Overview

Dataset statistics

Number of variables332
Number of observations1000
Missing cells170157
Missing cells (%)51.3%
Total size in memory14.9 MiB
Average record size in memory15.3 KiB

Variable types

Numeric1
Text330
Unsupported1

Alerts

qcarhybrid4 has constant value ""Constant
qcarhybrid5 has constant value ""Constant
qcarhybrid6 has constant value ""Constant
qcarincreasea9 has constant value ""Constant
qnoelectric8 has constant value ""Constant
qshare8 has constant value ""Constant
qridehail8 has constant value ""Constant
qbikestore9 has constant value ""Constant
qtransportnosubway11 has constant value ""Constant
qtransportnobus09 has constant value ""Constant
qtransportnobus10 has constant value ""Constant
qtransportnobus11 has constant value ""Constant
qdisability9 has constant value ""Constant
qschooltravelcode07 has constant value ""Constant
qschooltravelcode08 has constant value ""Constant
qschooltravelcode09 has constant value ""Constant
qschooltravelcode11 has constant value ""Constant
qschooltravelcode15 has constant value ""Constant
qschooltravelcode16 has constant value ""Constant
qschooltravelcode17 has constant value ""Constant
qschooltravelcode18 has constant value ""Constant
qschooltravelcode21 has constant value ""Constant
qschooltravelcode23 has constant value ""Constant
qschooltravelcode24 has constant value ""Constant
qschooltravelcode27 has constant value ""Constant
qschooltransitto5 has constant value ""Constant
qschooltransitto6 has constant value ""Constant
qschooltransitto7 has constant value ""Constant
qschooltransitfrom4 has constant value ""Constant
qschooltransitfrom5 has constant value ""Constant
qschooltransitfrom6 has constant value ""Constant
qschooltransitfrom7 has constant value ""Constant
qworktravelcode08 has constant value ""Constant
qworktravelcode10 has constant value ""Constant
qworktravelcode16 has constant value ""Constant
qworktravelcode20 has constant value ""Constant
qworktravelcode23 has constant value ""Constant
qworktravelcode26 has constant value ""Constant
qstudenttravelcode04 has constant value ""Constant
qstudenttravelcode06 has constant value ""Constant
qstudenttravelcode07 has constant value ""Constant
qstudenttravelcode08 has constant value ""Constant
qstudenttravelcode09 has constant value ""Constant
qstudenttravelcode10 has constant value ""Constant
qstudenttravelcode12 has constant value ""Constant
qstudenttravelcode14 has constant value ""Constant
qstudenttravelcode15 has constant value ""Constant
qstudenttravelcode18 has constant value ""Constant
qstudenttravelcode19 has constant value ""Constant
qstudenttravelcode20 has constant value ""Constant
qstudenttravelcode22 has constant value ""Constant
qstudenttravelcode23 has constant value ""Constant
qstudenttravelcode26 has constant value ""Constant
datacollection_starttime has 200 (20.0%) missing valuesMissing
qntacode has 116 (11.6%) missing valuesMissing
qcarmanynum has 399 (39.9%) missing valuesMissing
gcartype1_qcartype1_ma has 409 (40.9%) missing valuesMissing
gcartype1_qcartype2_ma has 815 (81.5%) missing valuesMissing
gcartype1_qcartype3_ma has 963 (96.3%) missing valuesMissing
gcartype1_qcartype4_ma has 989 (98.9%) missing valuesMissing
qcarhybrid1 has 993 (99.3%) missing valuesMissing
qcarhybrid2 has 993 (99.3%) missing valuesMissing
qcarhybrid3 has 993 (99.3%) missing valuesMissing
qcarhybrid4 has 993 (99.3%) missing valuesMissing
qcarhybrid5 has 993 (99.3%) missing valuesMissing
qcarhybrid6 has 993 (99.3%) missing valuesMissing
qcarchange has 100 (10.0%) missing valuesMissing
qcarreducea1 has 937 (93.7%) missing valuesMissing
qcarreducea2 has 937 (93.7%) missing valuesMissing
qcarreducea3 has 937 (93.7%) missing valuesMissing
qcarreducea4 has 937 (93.7%) missing valuesMissing
qcarreducea5 has 937 (93.7%) missing valuesMissing
qcarreducea6 has 937 (93.7%) missing valuesMissing
qcarreducea7 has 937 (93.7%) missing valuesMissing
qcarreducea8 has 937 (93.7%) missing valuesMissing
qcarreducea9 has 937 (93.7%) missing valuesMissing
qcarincreasea1 has 928 (92.8%) missing valuesMissing
qcarincreasea2 has 928 (92.8%) missing valuesMissing
qcarincreasea3 has 928 (92.8%) missing valuesMissing
qcarincreasea4 has 928 (92.8%) missing valuesMissing
qcarincreasea5 has 928 (92.8%) missing valuesMissing
qcarincreasea6 has 928 (92.8%) missing valuesMissing
qcarincreasea7 has 928 (92.8%) missing valuesMissing
qcarincreasea8 has 928 (92.8%) missing valuesMissing
qcarincreasea9 has 928 (92.8%) missing valuesMissing
qelectricconsider has 928 (92.8%) missing valuesMissing
qnoelectric1 has 943 (94.3%) missing valuesMissing
qnoelectric2 has 943 (94.3%) missing valuesMissing
qnoelectric3 has 943 (94.3%) missing valuesMissing
qnoelectric4 has 943 (94.3%) missing valuesMissing
qnoelectric5 has 943 (94.3%) missing valuesMissing
qnoelectric6 has 943 (94.3%) missing valuesMissing
qnoelectric7 has 943 (94.3%) missing valuesMissing
qnoelectric8 has 943 (94.3%) missing valuesMissing
gcarpark1_qcarpark1_ma has 403 (40.3%) missing valuesMissing
gcarpark1_qcarpark2_ma has 814 (81.4%) missing valuesMissing
gcarpark1_qcarpark3_ma has 962 (96.2%) missing valuesMissing
gcarpark1_qcarpark4_ma has 988 (98.8%) missing valuesMissing
qpaytopark has 883 (88.3%) missing valuesMissing
qpaytopark_amount has 927 (92.7%) missing valuesMissing
qtripplanapp has 106 (10.6%) missing valuesMissing
qridehail1 has 647 (64.7%) missing valuesMissing
qridehail2 has 647 (64.7%) missing valuesMissing
qridehail3 has 647 (64.7%) missing valuesMissing
qridehail4 has 647 (64.7%) missing valuesMissing
qridehail5 has 647 (64.7%) missing valuesMissing
qridehail6 has 647 (64.7%) missing valuesMissing
qridehail7 has 647 (64.7%) missing valuesMissing
qridehail8 has 647 (64.7%) missing valuesMissing
qridehail_freq has 814 (81.4%) missing valuesMissing
qridehailpurpose has 815 (81.5%) missing valuesMissing
qbikemany has 664 (66.4%) missing valuesMissing
qbiketype1 has 664 (66.4%) missing valuesMissing
qbiketype2 has 664 (66.4%) missing valuesMissing
qbiketype3 has 664 (66.4%) missing valuesMissing
qbiketype4 has 664 (66.4%) missing valuesMissing
qbiketype5 has 664 (66.4%) missing valuesMissing
qbikestore1 has 664 (66.4%) missing valuesMissing
qbikestore2 has 664 (66.4%) missing valuesMissing
qbikestore3 has 664 (66.4%) missing valuesMissing
qbikestore4 has 664 (66.4%) missing valuesMissing
qbikestore5 has 664 (66.4%) missing valuesMissing
qbikestore6 has 664 (66.4%) missing valuesMissing
qbikestore7 has 664 (66.4%) missing valuesMissing
qbikestore8 has 664 (66.4%) missing valuesMissing
qbikestore9 has 664 (66.4%) missing valuesMissing
qbikeride has 103 (10.3%) missing valuesMissing
qbiketo has 684 (68.4%) missing valuesMissing
qbikedays has 901 (90.1%) missing valuesMissing
qbikewhy1 has 809 (80.9%) missing valuesMissing
qbikewhy2 has 809 (80.9%) missing valuesMissing
qbikewhy3 has 809 (80.9%) missing valuesMissing
qbikewhy4 has 809 (80.9%) missing valuesMissing
qbikewhy5 has 809 (80.9%) missing valuesMissing
qbikewhy6 has 809 (80.9%) missing valuesMissing
qbikewhy7 has 809 (80.9%) missing valuesMissing
qbikewhy8 has 809 (80.9%) missing valuesMissing
qbikewhynot1 has 337 (33.7%) missing valuesMissing
qbikewhynot2 has 337 (33.7%) missing valuesMissing
qbikewhynot3 has 337 (33.7%) missing valuesMissing
qbikewhynot4 has 337 (33.7%) missing valuesMissing
qbikewhynot5 has 337 (33.7%) missing valuesMissing
qbikewhynot6 has 337 (33.7%) missing valuesMissing
qbikewhynot7 has 337 (33.7%) missing valuesMissing
qbikewhynot8 has 337 (33.7%) missing valuesMissing
qbikestolen has 16 (1.6%) missing valuesMissing
qcitibike has 40 (4.0%) missing valuesMissing
qcitibikefreq has 935 (93.5%) missing valuesMissing
gcitibk1_qcitibikeissues1 has 934 (93.4%) missing valuesMissing
gcitibk1_qcitibikeissues2 has 934 (93.4%) missing valuesMissing
qnocitibike01 has 106 (10.6%) missing valuesMissing
qnocitibike02 has 106 (10.6%) missing valuesMissing
qnocitibike03 has 106 (10.6%) missing valuesMissing
qnocitibike04 has 106 (10.6%) missing valuesMissing
qnocitibike05 has 106 (10.6%) missing valuesMissing
qnocitibike06 has 106 (10.6%) missing valuesMissing
qnocitibike07 has 106 (10.6%) missing valuesMissing
qnocitibike08 has 106 (10.6%) missing valuesMissing
qnocitibike09 has 106 (10.6%) missing valuesMissing
qnocitibike10 has 106 (10.6%) missing valuesMissing
qnocitibike11 has 106 (10.6%) missing valuesMissing
gfreight1b_qfreight1_ma has 119 (11.9%) missing valuesMissing
gfreight1b_qfreight2_ma has 50 (5.0%) missing valuesMissing
gfreight1b_qfreight3_ma has 142 (14.2%) missing valuesMissing
gfreight1b_qfreight4_ma has 41 (4.1%) missing valuesMissing
qpackagedeliver has 37 (3.7%) missing valuesMissing
qpostalstore has 838 (83.8%) missing valuesMissing
qsubwayservice has 82 (8.2%) missing valuesMissing
qsubwayimpact has 428 (42.8%) missing valuesMissing
qtransportnosubway01 has 783 (78.3%) missing valuesMissing
qtransportnosubway02 has 783 (78.3%) missing valuesMissing
qtransportnosubway03 has 783 (78.3%) missing valuesMissing
qtransportnosubway04 has 783 (78.3%) missing valuesMissing
qtransportnosubway05 has 783 (78.3%) missing valuesMissing
qtransportnosubway06 has 783 (78.3%) missing valuesMissing
qtransportnosubway07 has 783 (78.3%) missing valuesMissing
qtransportnosubway08 has 783 (78.3%) missing valuesMissing
qtransportnosubway09 has 783 (78.3%) missing valuesMissing
qtransportnosubway10 has 783 (78.3%) missing valuesMissing
qtransportnosubway11 has 783 (78.3%) missing valuesMissing
qbusservice has 149 (14.9%) missing valuesMissing
qbusimpact has 631 (63.1%) missing valuesMissing
qtransportnobus01 has 967 (96.7%) missing valuesMissing
qtransportnobus02 has 967 (96.7%) missing valuesMissing
qtransportnobus03 has 967 (96.7%) missing valuesMissing
qtransportnobus04 has 967 (96.7%) missing valuesMissing
qtransportnobus05 has 967 (96.7%) missing valuesMissing
qtransportnobus06 has 967 (96.7%) missing valuesMissing
qtransportnobus07 has 967 (96.7%) missing valuesMissing
qtransportnobus08 has 967 (96.7%) missing valuesMissing
qtransportnobus09 has 967 (96.7%) missing valuesMissing
qtransportnobus10 has 967 (96.7%) missing valuesMissing
qtransportnobus11 has 967 (96.7%) missing valuesMissing
qautovehiclefam has 31 (3.1%) missing valuesMissing
qautovehiclewill has 35 (3.5%) missing valuesMissing
qbuildingb has 15 (1.5%) missing valuesMissing
qrent has 33 (3.3%) missing valuesMissing
gchild1_qchild1_ma has 728 (72.8%) missing valuesMissing
gchild1_qchild2_ma has 874 (87.4%) missing valuesMissing
gchild1_qchild3_ma has 971 (97.1%) missing valuesMissing
gchild1_qchild4_ma has 991 (99.1%) missing valuesMissing
qchild1schooladdr has 789 (78.9%) missing valuesMissing
qchild2schooladdr has 905 (90.5%) missing valuesMissing
qchild3schooladdr has 982 (98.2%) missing valuesMissing
qchild4schooladdr has 996 (99.6%) missing valuesMissing
qaccompany has 789 (78.9%) missing valuesMissing
qschooltravelcode01 has 789 (78.9%) missing valuesMissing
qschooltravelcode02 has 789 (78.9%) missing valuesMissing
qschooltravelcode03 has 789 (78.9%) missing valuesMissing
qschooltravelcode04 has 789 (78.9%) missing valuesMissing
qschooltravelcode05 has 789 (78.9%) missing valuesMissing
qschooltravelcode06 has 789 (78.9%) missing valuesMissing
qschooltravelcode07 has 789 (78.9%) missing valuesMissing
qschooltravelcode08 has 789 (78.9%) missing valuesMissing
qschooltravelcode09 has 789 (78.9%) missing valuesMissing
qschooltravelcode10 has 789 (78.9%) missing valuesMissing
qschooltravelcode11 has 789 (78.9%) missing valuesMissing
qschooltravelcode12 has 789 (78.9%) missing valuesMissing
qschooltravelcode13 has 789 (78.9%) missing valuesMissing
qschooltravelcode14 has 789 (78.9%) missing valuesMissing
qschooltravelcode15 has 789 (78.9%) missing valuesMissing
qschooltravelcode16 has 789 (78.9%) missing valuesMissing
qschooltravelcode17 has 789 (78.9%) missing valuesMissing
qschooltravelcode18 has 789 (78.9%) missing valuesMissing
qschooltravelcode19 has 789 (78.9%) missing valuesMissing
qschooltravelcode20 has 789 (78.9%) missing valuesMissing
qschooltravelcode21 has 789 (78.9%) missing valuesMissing
qschooltravelcode22 has 789 (78.9%) missing valuesMissing
qschooltravelcode23 has 789 (78.9%) missing valuesMissing
qschooltravelcode24 has 789 (78.9%) missing valuesMissing
qschooltravelcode25 has 789 (78.9%) missing valuesMissing
qschooltravelcode26 has 789 (78.9%) missing valuesMissing
qschooltravelcode27 has 789 (78.9%) missing valuesMissing
qschooltransitto1 has 959 (95.9%) missing valuesMissing
qschooltransitto2 has 959 (95.9%) missing valuesMissing
qschooltransitto3 has 959 (95.9%) missing valuesMissing
qschooltransitto4 has 959 (95.9%) missing valuesMissing
qschooltransitto5 has 959 (95.9%) missing valuesMissing
qschooltransitto6 has 959 (95.9%) missing valuesMissing
qschooltransitto7 has 959 (95.9%) missing valuesMissing
qschooltransitfrom1 has 959 (95.9%) missing valuesMissing
qschooltransitfrom2 has 959 (95.9%) missing valuesMissing
qschooltransitfrom3 has 959 (95.9%) missing valuesMissing
qschooltransitfrom4 has 959 (95.9%) missing valuesMissing
qschooltransitfrom5 has 959 (95.9%) missing valuesMissing
qschooltransitfrom6 has 959 (95.9%) missing valuesMissing
qschooltransitfrom7 has 959 (95.9%) missing valuesMissing
qindustry has 406 (40.6%) missing valuesMissing
gfulltime_qfulltime_ma has 513 (51.3%) missing valuesMissing
gfulltime_qparttime_ma has 400 (40.0%) missing valuesMissing
qnumberofjobs has 293 (29.3%) missing valuesMissing
qworklocation has 401 (40.1%) missing valuesMissing
qworkfh has 402 (40.2%) missing valuesMissing
qborough_work1 has 540 (54.0%) missing valuesMissing
qntacode_work has 540 (54.0%) missing valuesMissing
qtimework has 454 (45.4%) missing valuesMissing
qtimehome has 454 (45.4%) missing valuesMissing
qborough_work2 has 921 (92.1%) missing valuesMissing
qntacode_work2 has 921 (92.1%) missing valuesMissing
qtimework2 has 910 (91.0%) missing valuesMissing
qtimehome2 has 910 (91.0%) missing valuesMissing
qborough_work3 has 977 (97.7%) missing valuesMissing
qntacode_work3 has 977 (97.7%) missing valuesMissing
qtimework3 has 977 (97.7%) missing valuesMissing
qtimehome3 has 977 (97.7%) missing valuesMissing
qworktravelcode01 has 451 (45.1%) missing valuesMissing
qworktravelcode02 has 451 (45.1%) missing valuesMissing
qworktravelcode03 has 451 (45.1%) missing valuesMissing
qworktravelcode04 has 451 (45.1%) missing valuesMissing
qworktravelcode05 has 451 (45.1%) missing valuesMissing
qworktravelcode06 has 451 (45.1%) missing valuesMissing
qworktravelcode07 has 451 (45.1%) missing valuesMissing
qworktravelcode08 has 451 (45.1%) missing valuesMissing
qworktravelcode09 has 451 (45.1%) missing valuesMissing
qworktravelcode10 has 451 (45.1%) missing valuesMissing
qworktravelcode11 has 451 (45.1%) missing valuesMissing
qworktravelcode12 has 451 (45.1%) missing valuesMissing
qworktravelcode13 has 451 (45.1%) missing valuesMissing
qworktravelcode14 has 451 (45.1%) missing valuesMissing
qworktravelcode15 has 451 (45.1%) missing valuesMissing
qworktravelcode16 has 451 (45.1%) missing valuesMissing
qworktravelcode17 has 451 (45.1%) missing valuesMissing
qworktravelcode18 has 451 (45.1%) missing valuesMissing
qworktravelcode19 has 451 (45.1%) missing valuesMissing
qworktravelcode20 has 451 (45.1%) missing valuesMissing
qworktravelcode21 has 451 (45.1%) missing valuesMissing
qworktravelcode22 has 451 (45.1%) missing valuesMissing
qworktravelcode23 has 451 (45.1%) missing valuesMissing
qworktravelcode24 has 451 (45.1%) missing valuesMissing
qworktravelcode25 has 451 (45.1%) missing valuesMissing
qworktravelcode26 has 451 (45.1%) missing valuesMissing
qworkcarpark has 839 (83.9%) missing valuesMissing
qworkparkpay has 841 (84.1%) missing valuesMissing
qworkbikepark has 989 (98.9%) missing valuesMissing
qlevelschool has 896 (89.6%) missing valuesMissing
qborough_school has 907 (90.7%) missing valuesMissing
qntacode_school has 907 (90.7%) missing valuesMissing
qstudentpark has 989 (98.9%) missing valuesMissing
qstudentparkpay has 989 (98.9%) missing valuesMissing
qstudentbikepark has 997 (99.7%) missing valuesMissing
qlanguagepref has 399 (39.9%) missing valuesMissing
qlanguage2 has 1000 (100.0%) missing valuesMissing
0 has unique valuesUnique
uniqueid has unique valuesUnique
qlanguage2 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-09 21:43:06.365573
Analysis finished2023-12-09 21:43:16.450097
Duration10.08 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

0
Real number (ℝ)

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean500.5
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2023-12-09T21:43:16.899817image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50.95
Q1250.75
median500.5
Q3750.25
95-th percentile950.05
Maximum1000
Range999
Interquartile range (IQR)499.5

Descriptive statistics

Standard deviation288.8194361
Coefficient of variation (CV)0.5770618104
Kurtosis-1.2
Mean500.5
Median Absolute Deviation (MAD)250
Skewness0
Sum500500
Variance83416.66667
MonotonicityStrictly increasing
2023-12-09T21:43:17.062616image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
672 1
 
0.1%
659 1
 
0.1%
660 1
 
0.1%
661 1
 
0.1%
662 1
 
0.1%
663 1
 
0.1%
664 1
 
0.1%
665 1
 
0.1%
666 1
 
0.1%
Other values (990) 990
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
ValueCountFrequency (%)
1000 1
0.1%
999 1
0.1%
998 1
0.1%
997 1
0.1%
996 1
0.1%

job
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size61.5 KiB
2023-12-09T21:43:17.514595image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.8
Min length5

Characters and Unicode

Total characters5800
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOnline
2nd rowOnline
3rd rowOnline
4th rowOnline
5th rowOnline
ValueCountFrequency (%)
online 800
80.0%
phone 200
 
20.0%
2023-12-09T21:43:17.797618image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1800
31.0%
e 1000
17.2%
O 800
13.8%
l 800
13.8%
i 800
13.8%
P 200
 
3.4%
h 200
 
3.4%
o 200
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4800
82.8%
Uppercase Letter 1000
 
17.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1800
37.5%
e 1000
20.8%
l 800
16.7%
i 800
16.7%
h 200
 
4.2%
o 200
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
O 800
80.0%
P 200
 
20.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5800
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1800
31.0%
e 1000
17.2%
O 800
13.8%
l 800
13.8%
i 800
13.8%
P 200
 
3.4%
h 200
 
3.4%
o 200
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1800
31.0%
e 1000
17.2%
O 800
13.8%
l 800
13.8%
i 800
13.8%
P 200
 
3.4%
h 200
 
3.4%
o 200
 
3.4%

datacollection_starttime
Text

MISSING 

Distinct800
Distinct (%)100.0%
Missing200
Missing (%)20.0%
Memory size59.5 KiB
2023-12-09T21:43:18.117673image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters8800
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique800 ?
Unique (%)100.0%

Sample

1st row13746130937
2nd row13749321989
3rd row13749324591
4th row13745513760
5th row13745174106
ValueCountFrequency (%)
13746285344 1
 
0.1%
13746286906 1
 
0.1%
13746287352 1
 
0.1%
13748191932 1
 
0.1%
13748653598 1
 
0.1%
13745513760 1
 
0.1%
13745254795 1
 
0.1%
13745898463 1
 
0.1%
13748237592 1
 
0.1%
13746351804 1
 
0.1%
Other values (790) 790
98.8%
2023-12-09T21:43:18.568166image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 1424
16.2%
1 1313
14.9%
3 1301
14.8%
4 1273
14.5%
5 641
7.3%
9 638
7.2%
6 606
6.9%
8 604
6.9%
0 511
 
5.8%
2 489
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8800
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 1424
16.2%
1 1313
14.9%
3 1301
14.8%
4 1273
14.5%
5 641
7.3%
9 638
7.2%
6 606
6.9%
8 604
6.9%
0 511
 
5.8%
2 489
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Common 8800
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 1424
16.2%
1 1313
14.9%
3 1301
14.8%
4 1273
14.5%
5 641
7.3%
9 638
7.2%
6 606
6.9%
8 604
6.9%
0 511
 
5.8%
2 489
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 1424
16.2%
1 1313
14.9%
3 1301
14.8%
4 1273
14.5%
5 641
7.3%
9 638
7.2%
6 606
6.9%
8 604
6.9%
0 511
 
5.8%
2 489
 
5.6%

uniqueid
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size62.0 KiB
2023-12-09T21:43:18.996859image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.4
Min length6

Characters and Unicode

Total characters6400
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st row100938
2nd row105388
3rd row105415
4th row100402
5th row100222
ValueCountFrequency (%)
100572 1
 
0.1%
10200147 1
 
0.1%
100432 1
 
0.1%
102586 1
 
0.1%
105377 1
 
0.1%
10200167 1
 
0.1%
100325 1
 
0.1%
101298 1
 
0.1%
101823 1
 
0.1%
103085 1
 
0.1%
Other values (990) 990
99.0%
2023-12-09T21:43:19.556246image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1989
31.1%
1 1438
22.5%
2 689
 
10.8%
3 479
 
7.5%
4 408
 
6.4%
5 323
 
5.0%
7 279
 
4.4%
8 272
 
4.2%
6 262
 
4.1%
9 261
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6400
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1989
31.1%
1 1438
22.5%
2 689
 
10.8%
3 479
 
7.5%
4 408
 
6.4%
5 323
 
5.0%
7 279
 
4.4%
8 272
 
4.2%
6 262
 
4.1%
9 261
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Common 6400
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1989
31.1%
1 1438
22.5%
2 689
 
10.8%
3 479
 
7.5%
4 408
 
6.4%
5 323
 
5.0%
7 279
 
4.4%
8 272
 
4.2%
6 262
 
4.1%
9 261
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1989
31.1%
1 1438
22.5%
2 689
 
10.8%
3 479
 
7.5%
4 408
 
6.4%
5 323
 
5.0%
7 279
 
4.4%
8 272
 
4.2%
6 262
 
4.1%
9 261
 
4.1%

qday
Text

Distinct7
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size62.6 KiB
2023-12-09T21:43:19.748495image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.982
Min length6

Characters and Unicode

Total characters6982
Distinct characters17
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFriday
2nd rowSunday
3rd rowSunday
4th rowFriday
5th rowMonday
ValueCountFrequency (%)
sunday 222
22.2%
saturday 159
15.9%
friday 149
14.9%
monday 143
14.3%
wednesday 119
11.9%
tuesday 109
10.9%
thursday 99
9.9%
2023-12-09T21:43:20.055460image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1159
16.6%
d 1119
16.0%
y 1000
14.3%
u 589
8.4%
n 484
6.9%
r 407
 
5.8%
S 381
 
5.5%
e 347
 
5.0%
s 327
 
4.7%
T 208
 
3.0%
Other values (7) 961
13.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5982
85.7%
Uppercase Letter 1000
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1159
19.4%
d 1119
18.7%
y 1000
16.7%
u 589
9.8%
n 484
8.1%
r 407
 
6.8%
e 347
 
5.8%
s 327
 
5.5%
t 159
 
2.7%
i 149
 
2.5%
Other values (2) 242
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
S 381
38.1%
T 208
20.8%
F 149
 
14.9%
M 143
 
14.3%
W 119
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 6982
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1159
16.6%
d 1119
16.0%
y 1000
14.3%
u 589
8.4%
n 484
6.9%
r 407
 
5.8%
S 381
 
5.5%
e 347
 
5.0%
s 327
 
4.7%
T 208
 
3.0%
Other values (7) 961
13.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6982
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1159
16.6%
d 1119
16.0%
y 1000
14.3%
u 589
8.4%
n 484
6.9%
r 407
 
5.8%
S 381
 
5.5%
e 347
 
5.0%
s 327
 
4.7%
T 208
 
3.0%
Other values (7) 961
13.8%

qntacode
Text

MISSING 

Distinct170
Distinct (%)19.2%
Missing116
Missing (%)11.6%
Memory size56.4 KiB
2023-12-09T21:43:20.475201image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters3536
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)2.7%

Sample

1st rowQN28
2nd rowQN54
3rd rowMN36
4th rowBX06
5th rowMN36
ValueCountFrequency (%)
qn17 34
 
3.8%
qn22 27
 
3.1%
qn70 24
 
2.7%
si24 22
 
2.5%
bk61 20
 
2.3%
mn12 19
 
2.1%
mn09 18
 
2.0%
mn36 16
 
1.8%
qn28 15
 
1.7%
si01 14
 
1.6%
Other values (160) 675
76.4%
2023-12-09T21:43:21.011502image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 465
13.2%
B 296
 
8.4%
Q 267
 
7.6%
2 261
 
7.4%
3 253
 
7.2%
1 251
 
7.1%
M 198
 
5.6%
0 196
 
5.5%
4 187
 
5.3%
X 171
 
4.8%
Other values (8) 991
28.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1768
50.0%
Decimal Number 1768
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 261
14.8%
3 253
14.3%
1 251
14.2%
0 196
11.1%
4 187
10.6%
6 157
8.9%
5 152
8.6%
7 147
8.3%
9 88
 
5.0%
8 76
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
N 465
26.3%
B 296
16.7%
Q 267
15.1%
M 198
11.2%
X 171
 
9.7%
K 125
 
7.1%
S 123
 
7.0%
I 123
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1768
50.0%
Common 1768
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 261
14.8%
3 253
14.3%
1 251
14.2%
0 196
11.1%
4 187
10.6%
6 157
8.9%
5 152
8.6%
7 147
8.3%
9 88
 
5.0%
8 76
 
4.3%
Latin
ValueCountFrequency (%)
N 465
26.3%
B 296
16.7%
Q 267
15.1%
M 198
11.2%
X 171
 
9.7%
K 125
 
7.1%
S 123
 
7.0%
I 123
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3536
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 465
13.2%
B 296
 
8.4%
Q 267
 
7.6%
2 261
 
7.4%
3 253
 
7.2%
1 251
 
7.1%
M 198
 
5.6%
0 196
 
5.5%
4 187
 
5.3%
X 171
 
4.8%
Other values (8) 991
28.0%

qgender
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size60.9 KiB
2023-12-09T21:43:21.174260image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.198
Min length4

Characters and Unicode

Total characters5198
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFemale
2nd rowMale
3rd rowMale
4th rowMale
5th rowMale
ValueCountFrequency (%)
female 599
59.9%
male 401
40.1%
2023-12-09T21:43:21.452358image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1599
30.8%
a 1000
19.2%
l 1000
19.2%
F 599
 
11.5%
m 599
 
11.5%
M 401
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4198
80.8%
Uppercase Letter 1000
 
19.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1599
38.1%
a 1000
23.8%
l 1000
23.8%
m 599
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
F 599
59.9%
M 401
40.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 5198
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1599
30.8%
a 1000
19.2%
l 1000
19.2%
F 599
 
11.5%
m 599
 
11.5%
M 401
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5198
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1599
30.8%
a 1000
19.2%
l 1000
19.2%
F 599
 
11.5%
m 599
 
11.5%
M 401
 
7.7%

qage
Text

Distinct77
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2023-12-09T21:43:21.749386image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.018
Min length2

Characters and Unicode

Total characters2018
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.9%

Sample

1st row38
2nd row55
3rd row65
4th row68
5th row50
ValueCountFrequency (%)
35 31
 
3.1%
34 29
 
2.9%
30 28
 
2.8%
52 27
 
2.7%
32 26
 
2.6%
27 25
 
2.5%
68 25
 
2.5%
40 24
 
2.4%
53 24
 
2.4%
51 22
 
2.2%
Other values (67) 739
73.9%
2023-12-09T21:43:22.180489image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 305
15.1%
5 299
14.8%
2 262
13.0%
4 254
12.6%
6 243
12.0%
7 154
7.6%
8 130
6.4%
9 127
6.3%
0 125
6.2%
1 119
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2018
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 305
15.1%
5 299
14.8%
2 262
13.0%
4 254
12.6%
6 243
12.0%
7 154
7.6%
8 130
6.4%
9 127
6.3%
0 125
6.2%
1 119
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Common 2018
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 305
15.1%
5 299
14.8%
2 262
13.0%
4 254
12.6%
6 243
12.0%
7 154
7.6%
8 130
6.4%
9 127
6.3%
0 125
6.2%
1 119
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2018
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 305
15.1%
5 299
14.8%
2 262
13.0%
4 254
12.6%
6 243
12.0%
7 154
7.6%
8 130
6.4%
9 127
6.3%
0 125
6.2%
1 119
 
5.9%

qagecode
Text

Distinct7
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
2023-12-09T21:43:22.372586image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length5
Mean length6.116
Min length5

Characters and Unicode

Total characters6116
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row35-44
2nd row55-64
3rd row65 or older
4th row65 or older
5th row45-54
ValueCountFrequency (%)
25-34 204
14.9%
45-54 193
14.1%
65 180
13.1%
or 180
13.1%
older 180
13.1%
35-44 178
13.0%
55-64 143
10.4%
18-24 93
6.8%
not 9
 
0.7%
coded 9
 
0.7%
2023-12-09T21:43:22.678710image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1234
20.2%
4 1182
19.3%
- 811
13.3%
3 382
 
6.2%
369
 
6.0%
o 360
 
5.9%
r 360
 
5.9%
6 323
 
5.3%
2 297
 
4.9%
e 180
 
2.9%
Other values (10) 618
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3604
58.9%
Lowercase Letter 1260
 
20.6%
Dash Punctuation 811
 
13.3%
Space Separator 369
 
6.0%
Uppercase Letter 72
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1234
34.2%
4 1182
32.8%
3 382
 
10.6%
6 323
 
9.0%
2 297
 
8.2%
1 93
 
2.6%
8 93
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
O 18
25.0%
D 18
25.0%
N 9
12.5%
T 9
12.5%
C 9
12.5%
E 9
12.5%
Lowercase Letter
ValueCountFrequency (%)
o 360
28.6%
r 360
28.6%
e 180
14.3%
d 180
14.3%
l 180
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 811
100.0%
Space Separator
ValueCountFrequency (%)
369
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4784
78.2%
Latin 1332
 
21.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 360
27.0%
r 360
27.0%
e 180
13.5%
d 180
13.5%
l 180
13.5%
O 18
 
1.4%
D 18
 
1.4%
N 9
 
0.7%
T 9
 
0.7%
C 9
 
0.7%
Common
ValueCountFrequency (%)
5 1234
25.8%
4 1182
24.7%
- 811
17.0%
3 382
 
8.0%
369
 
7.7%
6 323
 
6.8%
2 297
 
6.2%
1 93
 
1.9%
8 93
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6116
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1234
20.2%
4 1182
19.3%
- 811
13.3%
3 382
 
6.2%
369
 
6.0%
o 360
 
5.9%
r 360
 
5.9%
6 323
 
5.3%
2 297
 
4.9%
e 180
 
2.9%
Other values (10) 618
10.1%

qrace
Text

Distinct8
Distinct (%)0.8%
Missing3
Missing (%)0.3%
Memory size74.4 KiB
2023-12-09T21:43:22.874937image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length43
Median length15
Mean length19.21364092
Min length5

Characters and Unicode

Total characters19156
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st rowWhite/Caucasian
2nd rowWhite/Caucasian
3rd rowWhite/Caucasian
4th rowWhite/Caucasian
5th rowWhite/Caucasian
ValueCountFrequency (%)
white/caucasian 535
26.8%
american 435
21.8%
black 217
10.9%
african 217
10.9%
caribbean 217
10.9%
asian 127
 
6.4%
other 67
 
3.4%
or 44
 
2.2%
races 42
 
2.1%
more 42
 
2.1%
Other values (8) 56
 
2.8%
2023-12-09T21:43:23.198914image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3087
16.1%
i 2073
10.8%
n 1535
 
8.0%
c 1448
 
7.6%
e 1355
 
7.1%
r 1065
 
5.6%
1002
 
5.2%
/ 969
 
5.1%
A 780
 
4.1%
C 752
 
3.9%
Other values (22) 5090
26.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14779
77.2%
Uppercase Letter 2406
 
12.6%
Space Separator 1002
 
5.2%
Other Punctuation 969
 
5.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3087
20.9%
i 2073
14.0%
n 1535
10.4%
c 1448
9.8%
e 1355
9.2%
r 1065
 
7.2%
s 713
 
4.8%
t 604
 
4.1%
h 602
 
4.1%
u 542
 
3.7%
Other values (9) 1755
11.9%
Uppercase Letter
ValueCountFrequency (%)
A 780
32.4%
C 752
31.3%
W 535
22.2%
B 217
 
9.0%
O 67
 
2.8%
T 42
 
1.7%
R 7
 
0.3%
I 2
 
0.1%
N 2
 
0.1%
H 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1002
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 969
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17185
89.7%
Common 1971
 
10.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3087
18.0%
i 2073
12.1%
n 1535
8.9%
c 1448
 
8.4%
e 1355
 
7.9%
r 1065
 
6.2%
A 780
 
4.5%
C 752
 
4.4%
s 713
 
4.1%
t 604
 
3.5%
Other values (20) 3773
22.0%
Common
ValueCountFrequency (%)
1002
50.8%
/ 969
49.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 3087
16.1%
i 2073
10.8%
n 1535
 
8.0%
c 1448
 
7.6%
e 1355
 
7.1%
r 1065
 
5.6%
1002
 
5.2%
/ 969
 
5.1%
A 780
 
4.1%
C 752
 
3.9%
Other values (22) 5090
26.6%

qhispanic
Text

Distinct6
Distinct (%)0.6%
Missing4
Missing (%)0.4%
Memory size95.3 KiB
2023-12-09T21:43:23.414283image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length46
Median length46
Mean length40.6997992
Min length7

Characters and Unicode

Total characters40537
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo, not of Hispanic, Latino, or Spanish origin
2nd rowNo, not of Hispanic, Latino, or Spanish origin
3rd rowNo, not of Hispanic, Latino, or Spanish origin
4th rowNo, not of Hispanic, Latino, or Spanish origin
5th rowNo, not of Hispanic, Latino, or Spanish origin
ValueCountFrequency (%)
no 812
11.6%
not 812
11.6%
of 812
11.6%
hispanic 812
11.6%
latino 812
11.6%
or 812
11.6%
spanish 812
11.6%
origin 812
11.6%
yes 181
 
2.6%
puerto 94
 
1.3%
Other values (7) 256
 
3.6%
2023-12-09T21:43:24.012035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6031
14.9%
i 5062
12.5%
o 4990
12.3%
n 4260
10.5%
, 2665
 
6.6%
a 2636
 
6.5%
s 1808
 
4.5%
r 1795
 
4.4%
t 1771
 
4.4%
p 1624
 
4.0%
Other values (21) 7895
19.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 28062
69.2%
Space Separator 6031
 
14.9%
Uppercase Letter 3779
 
9.3%
Other Punctuation 2665
 
6.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 5062
18.0%
o 4990
17.8%
n 4260
15.2%
a 2636
9.4%
s 1808
 
6.4%
r 1795
 
6.4%
t 1771
 
6.3%
p 1624
 
5.8%
c 1002
 
3.6%
h 889
 
3.2%
Other values (8) 2225
7.9%
Uppercase Letter
ValueCountFrequency (%)
N 812
21.5%
S 812
21.5%
L 812
21.5%
H 812
21.5%
Y 181
 
4.8%
R 97
 
2.6%
P 94
 
2.5%
O 53
 
1.4%
M 48
 
1.3%
C 34
 
0.9%
Space Separator
ValueCountFrequency (%)
6031
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2665
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31841
78.5%
Common 8696
 
21.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 5062
15.9%
o 4990
15.7%
n 4260
13.4%
a 2636
8.3%
s 1808
 
5.7%
r 1795
 
5.6%
t 1771
 
5.6%
p 1624
 
5.1%
c 1002
 
3.1%
h 889
 
2.8%
Other values (19) 6004
18.9%
Common
ValueCountFrequency (%)
6031
69.4%
, 2665
30.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40537
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6031
14.9%
i 5062
12.5%
o 4990
12.3%
n 4260
10.5%
, 2665
 
6.6%
a 2636
 
6.5%
s 1808
 
4.5%
r 1795
 
4.4%
t 1771
 
4.4%
p 1624
 
4.0%
Other values (21) 7895
19.5%

qracecode
Text

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size72.4 KiB
2023-12-09T21:43:24.191696image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length24
Median length19
Mean length17.044
Min length8

Characters and Unicode

Total characters17044
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWhite, Non-Hispanic
2nd rowWhite, Non-Hispanic
3rd rowWhite, Non-Hispanic
4th rowWhite, Non-Hispanic
5th rowWhite, Non-Hispanic
ValueCountFrequency (%)
non-hispanic 819
44.9%
white 471
25.8%
hispanic 181
 
9.9%
black 178
 
9.7%
asian 123
 
6.7%
other 40
 
2.2%
don't 7
 
0.4%
know 7
 
0.4%
2023-12-09T21:43:24.494584image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 2594
15.2%
n 1956
11.5%
a 1301
 
7.6%
c 1178
 
6.9%
s 1123
 
6.6%
H 1000
 
5.9%
p 1000
 
5.9%
o 833
 
4.9%
826
 
4.8%
, 819
 
4.8%
Other values (15) 4414
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11935
70.0%
Uppercase Letter 2638
 
15.5%
Space Separator 826
 
4.8%
Other Punctuation 826
 
4.8%
Dash Punctuation 819
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 2594
21.7%
n 1956
16.4%
a 1301
10.9%
c 1178
9.9%
s 1123
9.4%
p 1000
 
8.4%
o 833
 
7.0%
t 518
 
4.3%
e 511
 
4.3%
h 511
 
4.3%
Other values (4) 410
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
H 1000
37.9%
N 819
31.0%
W 471
17.9%
B 178
 
6.7%
A 123
 
4.7%
O 40
 
1.5%
D 7
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 819
99.2%
' 7
 
0.8%
Space Separator
ValueCountFrequency (%)
826
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 819
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14573
85.5%
Common 2471
 
14.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 2594
17.8%
n 1956
13.4%
a 1301
8.9%
c 1178
8.1%
s 1123
7.7%
H 1000
 
6.9%
p 1000
 
6.9%
o 833
 
5.7%
N 819
 
5.6%
t 518
 
3.6%
Other values (11) 2251
15.4%
Common
ValueCountFrequency (%)
826
33.4%
, 819
33.1%
- 819
33.1%
' 7
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17044
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 2594
15.2%
n 1956
11.5%
a 1301
 
7.6%
c 1178
 
6.9%
s 1123
 
6.6%
H 1000
 
5.9%
p 1000
 
5.9%
o 833
 
4.9%
826
 
4.8%
, 819
 
4.8%
Other values (15) 4414
25.9%

qeducation
Text

Distinct7
Distinct (%)0.7%
Missing1
Missing (%)0.1%
Memory size98.7 KiB
2023-12-09T21:43:24.701808image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length57
Median length51
Mean length44.004004
Min length14

Characters and Unicode

Total characters43960
Distinct characters36
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGraduate degree (i.e., Master's, Professional, Doctorate)
2nd rowBachelor's degree (i.e., BA, BS, AB)
3rd rowBachelor's degree (i.e., BA, BS, AB)
4th rowSome college but degree not received or in progress
5th rowGraduate degree (i.e., Master's, Professional, Doctorate)
ValueCountFrequency (%)
degree 832
 
12.9%
i.e 798
 
12.4%
graduate 383
 
5.9%
bachelor's 332
 
5.1%
ba 332
 
5.1%
bs 332
 
5.1%
ab 332
 
5.1%
or 302
 
4.7%
master's 249
 
3.9%
professional 249
 
3.9%
Other values (16) 2309
35.8%
2023-12-09T21:43:25.022472image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 6307
14.3%
5451
 
12.4%
r 3100
 
7.1%
o 2752
 
6.3%
a 2062
 
4.7%
, 2043
 
4.6%
s 1997
 
4.5%
i 1767
 
4.0%
t 1683
 
3.8%
. 1596
 
3.6%
Other values (26) 15202
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 28221
64.2%
Space Separator 5451
 
12.4%
Uppercase Letter 4472
 
10.2%
Other Punctuation 4220
 
9.6%
Open Punctuation 798
 
1.8%
Close Punctuation 798
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6307
22.3%
r 3100
11.0%
o 2752
9.8%
a 2062
 
7.3%
s 1997
 
7.1%
i 1767
 
6.3%
t 1683
 
6.0%
g 1469
 
5.2%
d 1383
 
4.9%
l 1218
 
4.3%
Other values (10) 4483
15.9%
Uppercase Letter
ValueCountFrequency (%)
B 1328
29.7%
A 996
22.3%
S 607
13.6%
G 383
 
8.6%
D 383
 
8.6%
M 249
 
5.6%
P 249
 
5.6%
H 134
 
3.0%
E 134
 
3.0%
N 9
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 2043
48.4%
. 1596
37.8%
' 581
 
13.8%
Space Separator
ValueCountFrequency (%)
5451
100.0%
Open Punctuation
ValueCountFrequency (%)
( 798
100.0%
Close Punctuation
ValueCountFrequency (%)
) 798
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 32693
74.4%
Common 11267
 
25.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6307
19.3%
r 3100
 
9.5%
o 2752
 
8.4%
a 2062
 
6.3%
s 1997
 
6.1%
i 1767
 
5.4%
t 1683
 
5.1%
g 1469
 
4.5%
d 1383
 
4.2%
B 1328
 
4.1%
Other values (20) 8845
27.1%
Common
ValueCountFrequency (%)
5451
48.4%
, 2043
 
18.1%
. 1596
 
14.2%
( 798
 
7.1%
) 798
 
7.1%
' 581
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 6307
14.3%
5451
 
12.4%
r 3100
 
7.1%
o 2752
 
6.3%
a 2062
 
4.7%
, 2043
 
4.6%
s 1997
 
4.5%
i 1767
 
4.0%
t 1683
 
3.8%
. 1596
 
3.6%
Other values (26) 15202
34.6%

qincome
Text

Distinct10
Distinct (%)1.0%
Missing5
Missing (%)0.5%
Memory size72.2 KiB
2023-12-09T21:43:25.212525image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length17
Mean length16.9758794
Min length7

Characters and Unicode

Total characters16891
Distinct characters26
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row$150,000-$199,999
2nd row$100,000 - $149,999
3rd row$25,000 - $34,999
4th row$15,000 - $24,999
5th row$200,000 and above
ValueCountFrequency (%)
747
26.8%
100,000 165
 
5.9%
149,999 165
 
5.9%
50,000 164
 
5.9%
74,999 164
 
5.9%
75,000 142
 
5.1%
99,999 142
 
5.1%
35,000 115
 
4.1%
49,999 115
 
4.1%
14,999 85
 
3.0%
Other values (11) 787
28.2%
2023-12-09T21:43:25.521927image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 3335
19.7%
0 3285
19.4%
1796
10.6%
$ 1755
10.4%
, 1755
10.4%
- 802
 
4.7%
4 690
 
4.1%
5 637
 
3.8%
1 605
 
3.6%
7 306
 
1.8%
Other values (16) 1925
11.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9281
54.9%
Space Separator 1796
 
10.6%
Currency Symbol 1755
 
10.4%
Other Punctuation 1755
 
10.4%
Lowercase Letter 1375
 
8.1%
Dash Punctuation 802
 
4.7%
Uppercase Letter 127
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 235
17.1%
a 217
15.8%
s 212
15.4%
n 151
11.0%
d 108
7.9%
t 85
 
6.2%
h 85
 
6.2%
b 66
 
4.8%
o 66
 
4.8%
v 66
 
4.8%
Other values (2) 84
 
6.1%
Decimal Number
ValueCountFrequency (%)
9 3335
35.9%
0 3285
35.4%
4 690
 
7.4%
5 637
 
6.9%
1 605
 
6.5%
7 306
 
3.3%
2 227
 
2.4%
3 196
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
L 85
66.9%
R 42
33.1%
Space Separator
ValueCountFrequency (%)
1796
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1755
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1755
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 802
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15389
91.1%
Latin 1502
 
8.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 235
15.6%
a 217
14.4%
s 212
14.1%
n 151
10.1%
d 108
7.2%
t 85
 
5.7%
h 85
 
5.7%
L 85
 
5.7%
b 66
 
4.4%
o 66
 
4.4%
Other values (4) 192
12.8%
Common
ValueCountFrequency (%)
9 3335
21.7%
0 3285
21.3%
1796
11.7%
$ 1755
11.4%
, 1755
11.4%
- 802
 
5.2%
4 690
 
4.5%
5 637
 
4.1%
1 605
 
3.9%
7 306
 
2.0%
Other values (2) 423
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16891
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 3335
19.7%
0 3285
19.4%
1796
10.6%
$ 1755
10.4%
, 1755
10.4%
- 802
 
4.7%
4 690
 
4.1%
5 637
 
3.8%
1 605
 
3.6%
7 306
 
1.8%
Other values (16) 1925
11.4%

qsurveyzone
Text

Distinct11
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size69.3 KiB
2023-12-09T21:43:25.719541image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length14
Mean length13.843
Min length9

Characters and Unicode

Total characters13843
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowInner Queens
2nd rowInner Brooklyn
3rd rowNorthern Manhattan
4th rowInner Brooklyn
5th rowOuter Brooklyn
ValueCountFrequency (%)
queens 282
14.1%
northern 226
11.3%
manhattan 221
11.1%
bronx 187
9.3%
inner 186
9.3%
brooklyn 168
8.4%
outer 159
8.0%
staten 138
6.9%
island 138
6.9%
core 106
 
5.3%
Other values (4) 189
9.4%
2023-12-09T21:43:26.032170image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 2029
14.7%
e 1560
11.3%
r 1334
 
9.6%
t 1179
 
8.5%
1000
 
7.2%
a 939
 
6.8%
o 931
 
6.7%
h 523
 
3.8%
u 517
 
3.7%
s 420
 
3.0%
Other values (17) 3411
24.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10819
78.2%
Uppercase Letter 2024
 
14.6%
Space Separator 1000
 
7.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 2029
18.8%
e 1560
14.4%
r 1334
12.3%
t 1179
10.9%
a 939
8.7%
o 931
8.6%
h 523
 
4.8%
u 517
 
4.8%
s 420
 
3.9%
l 411
 
3.8%
Other values (5) 976
9.0%
Uppercase Letter
ValueCountFrequency (%)
B 355
17.5%
M 326
16.1%
I 324
16.0%
Q 282
13.9%
N 230
11.4%
S 214
10.6%
O 167
8.3%
C 110
 
5.4%
D 8
 
0.4%
T 4
 
0.2%
Space Separator
ValueCountFrequency (%)
1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12843
92.8%
Common 1000
 
7.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 2029
15.8%
e 1560
12.1%
r 1334
10.4%
t 1179
 
9.2%
a 939
 
7.3%
o 931
 
7.2%
h 523
 
4.1%
u 517
 
4.0%
s 420
 
3.3%
l 411
 
3.2%
Other values (16) 3000
23.4%
Common
ValueCountFrequency (%)
1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13843
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 2029
14.7%
e 1560
11.3%
r 1334
 
9.6%
t 1179
 
8.5%
1000
 
7.2%
a 939
 
6.8%
o 931
 
6.7%
h 523
 
3.8%
u 517
 
3.7%
s 420
 
3.0%
Other values (17) 3411
24.6%

qziphome
Text

Distinct161
Distinct (%)16.1%
Missing2
Missing (%)0.2%
Memory size60.6 KiB
2023-12-09T21:43:26.436697image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters4990
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)1.8%

Sample

1st row11372
2nd row11201
3rd row10039
4th row11205
5th row11235
ValueCountFrequency (%)
11375 30
 
3.0%
10314 25
 
2.5%
10312 23
 
2.3%
10025 17
 
1.7%
11377 17
 
1.7%
10453 16
 
1.6%
10027 15
 
1.5%
10033 15
 
1.5%
10306 15
 
1.5%
10009 13
 
1.3%
Other values (151) 812
81.4%
2023-12-09T21:43:26.947958image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1780
35.7%
0 1027
20.6%
3 523
 
10.5%
2 416
 
8.3%
4 394
 
7.9%
5 273
 
5.5%
7 209
 
4.2%
6 203
 
4.1%
9 87
 
1.7%
8 78
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4990
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1780
35.7%
0 1027
20.6%
3 523
 
10.5%
2 416
 
8.3%
4 394
 
7.9%
5 273
 
5.5%
7 209
 
4.2%
6 203
 
4.1%
9 87
 
1.7%
8 78
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 4990
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1780
35.7%
0 1027
20.6%
3 523
 
10.5%
2 416
 
8.3%
4 394
 
7.9%
5 273
 
5.5%
7 209
 
4.2%
6 203
 
4.1%
9 87
 
1.7%
8 78
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4990
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1780
35.7%
0 1027
20.6%
3 523
 
10.5%
2 416
 
8.3%
4 394
 
7.9%
5 273
 
5.5%
7 209
 
4.2%
6 203
 
4.1%
9 87
 
1.7%
8 78
 
1.6%

qborough
Text

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size64.1 KiB
2023-12-09T21:43:27.137676image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length13
Median length9
Mean length8.539
Min length6

Characters and Unicode

Total characters8539
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowQueens
2nd rowBrooklyn
3rd rowManhattan
4th rowBrooklyn
5th rowBrooklyn
ValueCountFrequency (%)
queens 282
21.3%
manhattan 228
17.2%
the 185
14.0%
bronx 185
14.0%
brooklyn 167
12.6%
staten 138
10.4%
island 138
10.4%
2023-12-09T21:43:27.447905image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1366
16.0%
a 960
11.2%
e 887
10.4%
t 732
 
8.6%
o 519
 
6.1%
s 420
 
4.9%
h 413
 
4.8%
B 352
 
4.1%
r 352
 
4.1%
323
 
3.8%
Other values (11) 2215
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6893
80.7%
Uppercase Letter 1323
 
15.5%
Space Separator 323
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1366
19.8%
a 960
13.9%
e 887
12.9%
t 732
10.6%
o 519
 
7.5%
s 420
 
6.1%
h 413
 
6.0%
r 352
 
5.1%
l 305
 
4.4%
u 282
 
4.1%
Other values (4) 657
9.5%
Uppercase Letter
ValueCountFrequency (%)
B 352
26.6%
Q 282
21.3%
M 228
17.2%
T 185
14.0%
S 138
 
10.4%
I 138
 
10.4%
Space Separator
ValueCountFrequency (%)
323
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8216
96.2%
Common 323
 
3.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1366
16.6%
a 960
11.7%
e 887
10.8%
t 732
 
8.9%
o 519
 
6.3%
s 420
 
5.1%
h 413
 
5.0%
B 352
 
4.3%
r 352
 
4.3%
l 305
 
3.7%
Other values (10) 1910
23.2%
Common
ValueCountFrequency (%)
323
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8539
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1366
16.0%
a 960
11.2%
e 887
10.4%
t 732
 
8.6%
o 519
 
6.1%
s 420
 
4.9%
h 413
 
4.8%
B 352
 
4.1%
r 352
 
4.1%
323
 
3.8%
Other values (11) 2215
25.9%

qlicense
Text

Distinct2
Distinct (%)0.2%
Missing5
Missing (%)0.5%
Memory size58.3 KiB
2023-12-09T21:43:27.570920image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.727638191
Min length2

Characters and Unicode

Total characters2714
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowNo
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 724
72.8%
no 271
 
27.2%
2023-12-09T21:43:27.808295image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 724
26.7%
e 724
26.7%
s 724
26.7%
N 271
 
10.0%
o 271
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1719
63.3%
Uppercase Letter 995
36.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 724
42.1%
s 724
42.1%
o 271
 
15.8%
Uppercase Letter
ValueCountFrequency (%)
Y 724
72.8%
N 271
 
27.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 2714
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 724
26.7%
e 724
26.7%
s 724
26.7%
N 271
 
10.0%
o 271
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2714
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 724
26.7%
e 724
26.7%
s 724
26.7%
N 271
 
10.0%
o 271
 
10.0%

qcaraccess
Text

Distinct4
Distinct (%)0.4%
Missing6
Missing (%)0.6%
Memory size94.7 KiB
2023-12-09T21:43:27.990359image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length104
Median length31
Mean length40.25452716
Min length5

Characters and Unicode

Total characters40013
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI do not personally own or lease a car, but I have access to a car belonging to a member of my household
2nd rowI do not have access to a car
3rd rowI do not have access to a car
4th rowI do not have access to a car
5th rowI do not have access to a car
ValueCountFrequency (%)
a 1258
13.3%
i 1113
11.7%
car 1113
11.7%
to 645
 
6.8%
personally 613
 
6.5%
own 613
 
6.5%
or 613
 
6.5%
lease 613
 
6.5%
access 500
 
5.3%
have 500
 
5.3%
Other values (9) 1896
20.0%
2023-12-09T21:43:28.298587image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8483
21.2%
a 4597
11.5%
o 4064
10.2%
e 3445
8.6%
r 2510
 
6.3%
s 2371
 
5.9%
l 2129
 
5.3%
c 2113
 
5.3%
n 2016
 
5.0%
t 1316
 
3.3%
Other values (15) 6969
17.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 30246
75.6%
Space Separator 8483
 
21.2%
Uppercase Letter 1139
 
2.8%
Other Punctuation 145
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4597
15.2%
o 4064
13.4%
e 3445
11.4%
r 2510
8.3%
s 2371
7.8%
l 2129
7.0%
c 2113
7.0%
n 2016
6.7%
t 1316
 
4.4%
h 816
 
2.7%
Other values (11) 4869
16.1%
Uppercase Letter
ValueCountFrequency (%)
I 1113
97.7%
O 26
 
2.3%
Space Separator
ValueCountFrequency (%)
8483
100.0%
Other Punctuation
ValueCountFrequency (%)
, 145
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31385
78.4%
Common 8628
 
21.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4597
14.6%
o 4064
12.9%
e 3445
11.0%
r 2510
8.0%
s 2371
7.6%
l 2129
 
6.8%
c 2113
 
6.7%
n 2016
 
6.4%
t 1316
 
4.2%
I 1113
 
3.5%
Other values (13) 5711
18.2%
Common
ValueCountFrequency (%)
8483
98.3%
, 145
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40013
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8483
21.2%
a 4597
11.5%
o 4064
10.2%
e 3445
8.6%
r 2510
 
6.3%
s 2371
 
5.9%
l 2129
 
5.3%
c 2113
 
5.3%
n 2016
 
5.0%
t 1316
 
3.3%
Other values (15) 6969
17.4%

qcarmanynum
Text

MISSING 

Distinct4
Distinct (%)0.7%
Missing399
Missing (%)39.9%
Memory size46.7 KiB
2023-12-09T21:43:28.422147image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.186356073
Min length1

Characters and Unicode

Total characters713
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row2
ValueCountFrequency (%)
1 412
65.5%
2 148
 
23.5%
3 27
 
4.3%
4 14
 
2.2%
or 14
 
2.2%
more 14
 
2.2%
2023-12-09T21:43:28.663507image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 412
57.8%
2 148
 
20.8%
28
 
3.9%
o 28
 
3.9%
r 28
 
3.9%
3 27
 
3.8%
4 14
 
2.0%
m 14
 
2.0%
e 14
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 601
84.3%
Lowercase Letter 84
 
11.8%
Space Separator 28
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 412
68.6%
2 148
 
24.6%
3 27
 
4.5%
4 14
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
o 28
33.3%
r 28
33.3%
m 14
16.7%
e 14
16.7%
Space Separator
ValueCountFrequency (%)
28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 629
88.2%
Latin 84
 
11.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 412
65.5%
2 148
 
23.5%
28
 
4.5%
3 27
 
4.3%
4 14
 
2.2%
Latin
ValueCountFrequency (%)
o 28
33.3%
r 28
33.3%
m 14
16.7%
e 14
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 713
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 412
57.8%
2 148
 
20.8%
28
 
3.9%
o 28
 
3.9%
r 28
 
3.9%
3 27
 
3.8%
4 14
 
2.0%
m 14
 
2.0%
e 14
 
2.0%

gcartype1_qcartype1_ma
Text

MISSING 

Distinct6
Distinct (%)1.0%
Missing409
Missing (%)40.9%
Memory size50.3 KiB
2023-12-09T21:43:28.824652image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length14
Median length8
Mean length7.873096447
Min length6

Characters and Unicode

Total characters4653
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st rowGasoline
2nd rowGasoline
3rd rowGasoline
4th rowGasoline
5th rowHybrid
ValueCountFrequency (%)
gasoline 543
91.7%
hybrid 35
 
5.9%
diesel 10
 
1.7%
all-electric 2
 
0.3%
refused 1
 
0.2%
plug-in 1
 
0.2%
2023-12-09T21:43:29.116536image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 591
12.7%
e 569
12.2%
l 560
12.0%
s 554
11.9%
n 544
11.7%
G 543
11.7%
o 543
11.7%
a 543
11.7%
r 37
 
0.8%
d 36
 
0.8%
Other values (15) 133
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4058
87.2%
Uppercase Letter 591
 
12.7%
Dash Punctuation 3
 
0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 591
14.6%
e 569
14.0%
l 560
13.8%
s 554
13.7%
n 544
13.4%
o 543
13.4%
a 543
13.4%
r 37
 
0.9%
d 36
 
0.9%
b 35
 
0.9%
Other values (7) 46
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
G 543
91.9%
H 34
 
5.8%
D 10
 
1.7%
A 2
 
0.3%
R 1
 
0.2%
P 1
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4649
99.9%
Common 4
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 591
12.7%
e 569
12.2%
l 560
12.0%
s 554
11.9%
n 544
11.7%
G 543
11.7%
o 543
11.7%
a 543
11.7%
r 37
 
0.8%
d 36
 
0.8%
Other values (13) 129
 
2.8%
Common
ValueCountFrequency (%)
- 3
75.0%
1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4653
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 591
12.7%
e 569
12.2%
l 560
12.0%
s 554
11.9%
n 544
11.7%
G 543
11.7%
o 543
11.7%
a 543
11.7%
r 37
 
0.8%
d 36
 
0.8%
Other values (15) 133
 
2.9%

gcartype1_qcartype2_ma
Text

MISSING 

Distinct6
Distinct (%)3.2%
Missing815
Missing (%)81.5%
Memory size37.3 KiB
2023-12-09T21:43:29.280631image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length14
Median length8
Mean length8.027027027
Min length6

Characters and Unicode

Total characters1485
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.1%

Sample

1st rowGasoline
2nd rowGasoline
3rd rowHybrid
4th rowGasoline
5th rowGasoline
ValueCountFrequency (%)
gasoline 168
88.9%
hybrid 11
 
5.8%
diesel 4
 
2.1%
plug-in 4
 
2.1%
all-electric 1
 
0.5%
refused 1
 
0.5%
2023-12-09T21:43:29.589540image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 188
12.7%
e 180
12.1%
l 179
12.1%
s 173
11.6%
n 172
11.6%
G 168
11.3%
o 168
11.3%
a 168
11.3%
r 12
 
0.8%
d 12
 
0.8%
Other values (15) 65
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1291
86.9%
Uppercase Letter 185
 
12.5%
Dash Punctuation 5
 
0.3%
Space Separator 4
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 188
14.6%
e 180
13.9%
l 179
13.9%
s 173
13.4%
n 172
13.3%
o 168
13.0%
a 168
13.0%
r 12
 
0.9%
d 12
 
0.9%
b 11
 
0.9%
Other values (7) 28
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
G 168
90.8%
H 7
 
3.8%
D 4
 
2.2%
P 4
 
2.2%
A 1
 
0.5%
R 1
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1476
99.4%
Common 9
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 188
12.7%
e 180
12.2%
l 179
12.1%
s 173
11.7%
n 172
11.7%
G 168
11.4%
o 168
11.4%
a 168
11.4%
r 12
 
0.8%
d 12
 
0.8%
Other values (13) 56
 
3.8%
Common
ValueCountFrequency (%)
- 5
55.6%
4
44.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1485
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 188
12.7%
e 180
12.1%
l 179
12.1%
s 173
11.6%
n 172
11.6%
G 168
11.3%
o 168
11.3%
a 168
11.3%
r 12
 
0.8%
d 12
 
0.8%
Other values (15) 65
 
4.4%

gcartype1_qcartype3_ma
Text

MISSING 

Distinct3
Distinct (%)8.1%
Missing963
Missing (%)96.3%
Memory size32.6 KiB
2023-12-09T21:43:29.746242image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.675675676
Min length6

Characters and Unicode

Total characters284
Distinct characters14
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGasoline
2nd rowGasoline
3rd rowGasoline
4th rowHybrid
5th rowGasoline
ValueCountFrequency (%)
gasoline 31
83.8%
diesel 3
 
8.1%
hybrid 3
 
8.1%
2023-12-09T21:43:30.033175image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 37
13.0%
e 37
13.0%
s 34
12.0%
l 34
12.0%
G 31
10.9%
a 31
10.9%
o 31
10.9%
n 31
10.9%
D 3
 
1.1%
H 3
 
1.1%
Other values (4) 12
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 247
87.0%
Uppercase Letter 37
 
13.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 37
15.0%
e 37
15.0%
s 34
13.8%
l 34
13.8%
a 31
12.6%
o 31
12.6%
n 31
12.6%
y 3
 
1.2%
b 3
 
1.2%
r 3
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
G 31
83.8%
D 3
 
8.1%
H 3
 
8.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 284
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 37
13.0%
e 37
13.0%
s 34
12.0%
l 34
12.0%
G 31
10.9%
a 31
10.9%
o 31
10.9%
n 31
10.9%
D 3
 
1.1%
H 3
 
1.1%
Other values (4) 12
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 284
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 37
13.0%
e 37
13.0%
s 34
12.0%
l 34
12.0%
G 31
10.9%
a 31
10.9%
o 31
10.9%
n 31
10.9%
D 3
 
1.1%
H 3
 
1.1%
Other values (4) 12
 
4.2%

gcartype1_qcartype4_ma
Text

MISSING 

Distinct2
Distinct (%)18.2%
Missing989
Missing (%)98.9%
Memory size31.7 KiB
2023-12-09T21:43:30.187438image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.818181818
Min length6

Characters and Unicode

Total characters86
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)9.1%

Sample

1st rowGasoline
2nd rowGasoline
3rd rowGasoline
4th rowGasoline
5th rowGasoline
ValueCountFrequency (%)
gasoline 10
90.9%
diesel 1
 
9.1%
2023-12-09T21:43:30.481809image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 12
14.0%
s 11
12.8%
l 11
12.8%
i 11
12.8%
G 10
11.6%
a 10
11.6%
o 10
11.6%
n 10
11.6%
D 1
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 75
87.2%
Uppercase Letter 11
 
12.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 12
16.0%
s 11
14.7%
l 11
14.7%
i 11
14.7%
a 10
13.3%
o 10
13.3%
n 10
13.3%
Uppercase Letter
ValueCountFrequency (%)
G 10
90.9%
D 1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 86
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 12
14.0%
s 11
12.8%
l 11
12.8%
i 11
12.8%
G 10
11.6%
a 10
11.6%
o 10
11.6%
n 10
11.6%
D 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 12
14.0%
s 11
12.8%
l 11
12.8%
i 11
12.8%
G 10
11.6%
a 10
11.6%
o 10
11.6%
n 10
11.6%
D 1
 
1.2%

qcarhybrid1
Text

MISSING 

Distinct2
Distinct (%)28.6%
Missing993
Missing (%)99.3%
Memory size31.6 KiB
2023-12-09T21:43:30.599120image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.857142857
Min length2

Characters and Unicode

Total characters20
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)14.3%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowYes
5th rowNo
ValueCountFrequency (%)
yes 6
85.7%
no 1
 
14.3%
2023-12-09T21:43:30.831241image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 6
30.0%
e 6
30.0%
s 6
30.0%
N 1
 
5.0%
o 1
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13
65.0%
Uppercase Letter 7
35.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6
46.2%
s 6
46.2%
o 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
Y 6
85.7%
N 1
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 20
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 6
30.0%
e 6
30.0%
s 6
30.0%
N 1
 
5.0%
o 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 6
30.0%
e 6
30.0%
s 6
30.0%
N 1
 
5.0%
o 1
 
5.0%

qcarhybrid2
Text

MISSING 

Distinct2
Distinct (%)28.6%
Missing993
Missing (%)99.3%
Memory size31.6 KiB
2023-12-09T21:43:30.950002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.571428571
Min length2

Characters and Unicode

Total characters18
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowYes
3rd rowYes
4th rowNo
5th rowYes
ValueCountFrequency (%)
yes 4
57.1%
no 3
42.9%
2023-12-09T21:43:31.488647image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 4
22.2%
e 4
22.2%
s 4
22.2%
N 3
16.7%
o 3
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11
61.1%
Uppercase Letter 7
38.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
36.4%
s 4
36.4%
o 3
27.3%
Uppercase Letter
ValueCountFrequency (%)
Y 4
57.1%
N 3
42.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 18
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 4
22.2%
e 4
22.2%
s 4
22.2%
N 3
16.7%
o 3
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 4
22.2%
e 4
22.2%
s 4
22.2%
N 3
16.7%
o 3
16.7%

qcarhybrid3
Text

MISSING 

Distinct2
Distinct (%)28.6%
Missing993
Missing (%)99.3%
Memory size31.6 KiB
2023-12-09T21:43:31.612687image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.285714286
Min length2

Characters and Unicode

Total characters16
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 5
71.4%
yes 2
 
28.6%
2023-12-09T21:43:31.844574image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 5
31.2%
o 5
31.2%
Y 2
 
12.5%
e 2
 
12.5%
s 2
 
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9
56.2%
Uppercase Letter 7
43.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 5
55.6%
e 2
 
22.2%
s 2
 
22.2%
Uppercase Letter
ValueCountFrequency (%)
N 5
71.4%
Y 2
 
28.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 16
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 5
31.2%
o 5
31.2%
Y 2
 
12.5%
e 2
 
12.5%
s 2
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 5
31.2%
o 5
31.2%
Y 2
 
12.5%
e 2
 
12.5%
s 2
 
12.5%

qcarhybrid4
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)14.3%
Missing993
Missing (%)99.3%
Memory size31.6 KiB
2023-12-09T21:43:31.946020image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters14
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 7
100.0%
2023-12-09T21:43:32.170252image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 7
50.0%
o 7
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7
50.0%
Lowercase Letter 7
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 7
50.0%
o 7
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 7
50.0%
o 7
50.0%

qcarhybrid5
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)14.3%
Missing993
Missing (%)99.3%
Memory size31.6 KiB
2023-12-09T21:43:32.276108image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters14
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 7
100.0%
2023-12-09T21:43:32.505986image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 7
50.0%
o 7
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7
50.0%
Lowercase Letter 7
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 7
50.0%
o 7
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 7
50.0%
o 7
50.0%

qcarhybrid6
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)14.3%
Missing993
Missing (%)99.3%
Memory size31.6 KiB
2023-12-09T21:43:32.608623image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters14
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 7
100.0%
2023-12-09T21:43:32.818297image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 7
50.0%
o 7
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7
50.0%
Lowercase Letter 7
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 7
50.0%
o 7
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 7
50.0%
o 7
50.0%

qcarchange
Text

MISSING 

Distinct3
Distinct (%)0.3%
Missing100
Missing (%)10.0%
Memory size78.6 KiB
2023-12-09T21:43:33.015284image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length26
Mean length28.71
Min length26

Characters and Unicode

Total characters25839
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThe number has not changed
2nd rowThe number has not changed
3rd rowThe number has not changed
4th rowThe number has not changed
5th rowThe number has not changed
ValueCountFrequency (%)
the 900
17.9%
number 900
17.9%
has 900
17.9%
not 765
15.2%
changed 765
15.2%
of 135
 
2.7%
cars 135
 
2.7%
it 135
 
2.7%
access 135
 
2.7%
to 135
 
2.7%
Other values (2) 135
 
2.7%
2023-12-09T21:43:33.344411image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4140
16.0%
e 2970
11.5%
h 2565
9.9%
n 2502
9.7%
a 2007
 
7.8%
s 1377
 
5.3%
c 1305
 
5.1%
t 1170
 
4.5%
r 1107
 
4.3%
o 1035
 
4.0%
Other values (10) 5661
21.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20799
80.5%
Space Separator 4140
 
16.0%
Uppercase Letter 900
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2970
14.3%
h 2565
12.3%
n 2502
12.0%
a 2007
9.6%
s 1377
 
6.6%
c 1305
 
6.3%
t 1170
 
5.6%
r 1107
 
5.3%
o 1035
 
5.0%
d 963
 
4.6%
Other values (6) 3798
18.3%
Uppercase Letter
ValueCountFrequency (%)
T 765
85.0%
I 72
 
8.0%
R 63
 
7.0%
Space Separator
ValueCountFrequency (%)
4140
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21699
84.0%
Common 4140
 
16.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2970
13.7%
h 2565
11.8%
n 2502
11.5%
a 2007
9.2%
s 1377
 
6.3%
c 1305
 
6.0%
t 1170
 
5.4%
r 1107
 
5.1%
o 1035
 
4.8%
d 963
 
4.4%
Other values (9) 4698
21.7%
Common
ValueCountFrequency (%)
4140
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25839
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4140
16.0%
e 2970
11.5%
h 2565
9.9%
n 2502
9.7%
a 2007
 
7.8%
s 1377
 
5.3%
c 1305
 
5.1%
t 1170
 
4.5%
r 1107
 
4.3%
o 1035
 
4.0%
Other values (10) 5661
21.9%

qcarreducea1
Text

MISSING 

Distinct2
Distinct (%)3.2%
Missing937
Missing (%)93.7%
Memory size33.1 KiB
2023-12-09T21:43:33.468627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.301587302
Min length2

Characters and Unicode

Total characters145
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowNo
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 44
69.8%
yes 19
30.2%
2023-12-09T21:43:33.697582image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 44
30.3%
o 44
30.3%
Y 19
13.1%
e 19
13.1%
s 19
13.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 82
56.6%
Uppercase Letter 63
43.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 44
53.7%
e 19
23.2%
s 19
23.2%
Uppercase Letter
ValueCountFrequency (%)
N 44
69.8%
Y 19
30.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 145
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 44
30.3%
o 44
30.3%
Y 19
13.1%
e 19
13.1%
s 19
13.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 145
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 44
30.3%
o 44
30.3%
Y 19
13.1%
e 19
13.1%
s 19
13.1%

qcarreducea2
Text

MISSING 

Distinct2
Distinct (%)3.2%
Missing937
Missing (%)93.7%
Memory size33.1 KiB
2023-12-09T21:43:33.818492image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.301587302
Min length2

Characters and Unicode

Total characters145
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 44
69.8%
yes 19
30.2%
2023-12-09T21:43:34.050480image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 44
30.3%
o 44
30.3%
Y 19
13.1%
e 19
13.1%
s 19
13.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 82
56.6%
Uppercase Letter 63
43.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 44
53.7%
e 19
23.2%
s 19
23.2%
Uppercase Letter
ValueCountFrequency (%)
N 44
69.8%
Y 19
30.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 145
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 44
30.3%
o 44
30.3%
Y 19
13.1%
e 19
13.1%
s 19
13.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 145
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 44
30.3%
o 44
30.3%
Y 19
13.1%
e 19
13.1%
s 19
13.1%

qcarreducea3
Text

MISSING 

Distinct2
Distinct (%)3.2%
Missing937
Missing (%)93.7%
Memory size33.1 KiB
2023-12-09T21:43:34.187455image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.428571429
Min length2

Characters and Unicode

Total characters153
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 36
57.1%
yes 27
42.9%
2023-12-09T21:43:34.438528image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 36
23.5%
o 36
23.5%
Y 27
17.6%
e 27
17.6%
s 27
17.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 90
58.8%
Uppercase Letter 63
41.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 36
40.0%
e 27
30.0%
s 27
30.0%
Uppercase Letter
ValueCountFrequency (%)
N 36
57.1%
Y 27
42.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 153
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 36
23.5%
o 36
23.5%
Y 27
17.6%
e 27
17.6%
s 27
17.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 153
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 36
23.5%
o 36
23.5%
Y 27
17.6%
e 27
17.6%
s 27
17.6%

qcarreducea4
Text

MISSING 

Distinct2
Distinct (%)3.2%
Missing937
Missing (%)93.7%
Memory size33.0 KiB
2023-12-09T21:43:34.549926image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.111111111
Min length2

Characters and Unicode

Total characters133
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 56
88.9%
yes 7
 
11.1%
2023-12-09T21:43:34.773212image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 56
42.1%
o 56
42.1%
Y 7
 
5.3%
e 7
 
5.3%
s 7
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 70
52.6%
Uppercase Letter 63
47.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 56
80.0%
e 7
 
10.0%
s 7
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
N 56
88.9%
Y 7
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 133
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 56
42.1%
o 56
42.1%
Y 7
 
5.3%
e 7
 
5.3%
s 7
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 133
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 56
42.1%
o 56
42.1%
Y 7
 
5.3%
e 7
 
5.3%
s 7
 
5.3%

qcarreducea5
Text

MISSING 

Distinct2
Distinct (%)3.2%
Missing937
Missing (%)93.7%
Memory size33.0 KiB
2023-12-09T21:43:34.879964image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.031746032
Min length2

Characters and Unicode

Total characters128
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 61
96.8%
yes 2
 
3.2%
2023-12-09T21:43:35.104856image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 61
47.7%
o 61
47.7%
Y 2
 
1.6%
e 2
 
1.6%
s 2
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 65
50.8%
Uppercase Letter 63
49.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 61
93.8%
e 2
 
3.1%
s 2
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
N 61
96.8%
Y 2
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 128
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 61
47.7%
o 61
47.7%
Y 2
 
1.6%
e 2
 
1.6%
s 2
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 128
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 61
47.7%
o 61
47.7%
Y 2
 
1.6%
e 2
 
1.6%
s 2
 
1.6%

qcarreducea6
Text

MISSING 

Distinct2
Distinct (%)3.2%
Missing937
Missing (%)93.7%
Memory size33.0 KiB
2023-12-09T21:43:35.216519image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.095238095
Min length2

Characters and Unicode

Total characters132
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 57
90.5%
yes 6
 
9.5%
2023-12-09T21:43:35.439541image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 57
43.2%
o 57
43.2%
Y 6
 
4.5%
e 6
 
4.5%
s 6
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 69
52.3%
Uppercase Letter 63
47.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 57
82.6%
e 6
 
8.7%
s 6
 
8.7%
Uppercase Letter
ValueCountFrequency (%)
N 57
90.5%
Y 6
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 132
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 57
43.2%
o 57
43.2%
Y 6
 
4.5%
e 6
 
4.5%
s 6
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 132
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 57
43.2%
o 57
43.2%
Y 6
 
4.5%
e 6
 
4.5%
s 6
 
4.5%

qcarreducea7
Text

MISSING 

Distinct2
Distinct (%)3.2%
Missing937
Missing (%)93.7%
Memory size33.0 KiB
2023-12-09T21:43:35.550029image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.095238095
Min length2

Characters and Unicode

Total characters132
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 57
90.5%
yes 6
 
9.5%
2023-12-09T21:43:35.771401image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 57
43.2%
o 57
43.2%
Y 6
 
4.5%
e 6
 
4.5%
s 6
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 69
52.3%
Uppercase Letter 63
47.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 57
82.6%
e 6
 
8.7%
s 6
 
8.7%
Uppercase Letter
ValueCountFrequency (%)
N 57
90.5%
Y 6
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 132
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 57
43.2%
o 57
43.2%
Y 6
 
4.5%
e 6
 
4.5%
s 6
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 132
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 57
43.2%
o 57
43.2%
Y 6
 
4.5%
e 6
 
4.5%
s 6
 
4.5%

qcarreducea8
Text

MISSING 

Distinct2
Distinct (%)3.2%
Missing937
Missing (%)93.7%
Memory size33.0 KiB
2023-12-09T21:43:35.883441image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.015873016
Min length2

Characters and Unicode

Total characters127
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 62
98.4%
yes 1
 
1.6%
2023-12-09T21:43:36.120618image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 62
48.8%
o 62
48.8%
Y 1
 
0.8%
e 1
 
0.8%
s 1
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 64
50.4%
Uppercase Letter 63
49.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 62
96.9%
e 1
 
1.6%
s 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
N 62
98.4%
Y 1
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 127
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 62
48.8%
o 62
48.8%
Y 1
 
0.8%
e 1
 
0.8%
s 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 127
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 62
48.8%
o 62
48.8%
Y 1
 
0.8%
e 1
 
0.8%
s 1
 
0.8%

qcarreducea9
Text

MISSING 

Distinct2
Distinct (%)3.2%
Missing937
Missing (%)93.7%
Memory size33.0 KiB
2023-12-09T21:43:36.233824image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.015873016
Min length2

Characters and Unicode

Total characters127
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 62
98.4%
yes 1
 
1.6%
2023-12-09T21:43:36.467974image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 62
48.8%
o 62
48.8%
Y 1
 
0.8%
e 1
 
0.8%
s 1
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 64
50.4%
Uppercase Letter 63
49.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 62
96.9%
e 1
 
1.6%
s 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
N 62
98.4%
Y 1
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 127
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 62
48.8%
o 62
48.8%
Y 1
 
0.8%
e 1
 
0.8%
s 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 127
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 62
48.8%
o 62
48.8%
Y 1
 
0.8%
e 1
 
0.8%
s 1
 
0.8%

qcarincreasea1
Text

MISSING 

Distinct2
Distinct (%)2.8%
Missing928
Missing (%)92.8%
Memory size33.3 KiB
2023-12-09T21:43:36.591524image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.277777778
Min length2

Characters and Unicode

Total characters164
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 52
72.2%
yes 20
 
27.8%
2023-12-09T21:43:36.824623image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 52
31.7%
o 52
31.7%
Y 20
 
12.2%
e 20
 
12.2%
s 20
 
12.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 92
56.1%
Uppercase Letter 72
43.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 52
56.5%
e 20
 
21.7%
s 20
 
21.7%
Uppercase Letter
ValueCountFrequency (%)
N 52
72.2%
Y 20
 
27.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 164
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 52
31.7%
o 52
31.7%
Y 20
 
12.2%
e 20
 
12.2%
s 20
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 164
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 52
31.7%
o 52
31.7%
Y 20
 
12.2%
e 20
 
12.2%
s 20
 
12.2%

qcarincreasea2
Text

MISSING 

Distinct2
Distinct (%)2.8%
Missing928
Missing (%)92.8%
Memory size33.3 KiB
2023-12-09T21:43:36.945998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.291666667
Min length2

Characters and Unicode

Total characters165
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 51
70.8%
yes 21
29.2%
2023-12-09T21:43:37.180995image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 51
30.9%
o 51
30.9%
Y 21
12.7%
e 21
12.7%
s 21
12.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 93
56.4%
Uppercase Letter 72
43.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 51
54.8%
e 21
22.6%
s 21
22.6%
Uppercase Letter
ValueCountFrequency (%)
N 51
70.8%
Y 21
29.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 165
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 51
30.9%
o 51
30.9%
Y 21
12.7%
e 21
12.7%
s 21
12.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 165
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 51
30.9%
o 51
30.9%
Y 21
12.7%
e 21
12.7%
s 21
12.7%

qcarincreasea3
Text

MISSING 

Distinct2
Distinct (%)2.8%
Missing928
Missing (%)92.8%
Memory size33.3 KiB
2023-12-09T21:43:37.297121image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.194444444
Min length2

Characters and Unicode

Total characters158
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 58
80.6%
yes 14
 
19.4%
2023-12-09T21:43:37.533362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 58
36.7%
o 58
36.7%
Y 14
 
8.9%
e 14
 
8.9%
s 14
 
8.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 86
54.4%
Uppercase Letter 72
45.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 58
67.4%
e 14
 
16.3%
s 14
 
16.3%
Uppercase Letter
ValueCountFrequency (%)
N 58
80.6%
Y 14
 
19.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 158
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 58
36.7%
o 58
36.7%
Y 14
 
8.9%
e 14
 
8.9%
s 14
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 158
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 58
36.7%
o 58
36.7%
Y 14
 
8.9%
e 14
 
8.9%
s 14
 
8.9%

qcarincreasea4
Text

MISSING 

Distinct2
Distinct (%)2.8%
Missing928
Missing (%)92.8%
Memory size33.3 KiB
2023-12-09T21:43:37.644900image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.097222222
Min length2

Characters and Unicode

Total characters151
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 65
90.3%
yes 7
 
9.7%
2023-12-09T21:43:37.871293image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 65
43.0%
o 65
43.0%
Y 7
 
4.6%
e 7
 
4.6%
s 7
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 79
52.3%
Uppercase Letter 72
47.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 65
82.3%
e 7
 
8.9%
s 7
 
8.9%
Uppercase Letter
ValueCountFrequency (%)
N 65
90.3%
Y 7
 
9.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 151
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 65
43.0%
o 65
43.0%
Y 7
 
4.6%
e 7
 
4.6%
s 7
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 151
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 65
43.0%
o 65
43.0%
Y 7
 
4.6%
e 7
 
4.6%
s 7
 
4.6%

qcarincreasea5
Text

MISSING 

Distinct2
Distinct (%)2.8%
Missing928
Missing (%)92.8%
Memory size33.3 KiB
2023-12-09T21:43:37.978292image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.041666667
Min length2

Characters and Unicode

Total characters147
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 69
95.8%
yes 3
 
4.2%
2023-12-09T21:43:38.581130image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 69
46.9%
o 69
46.9%
Y 3
 
2.0%
e 3
 
2.0%
s 3
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 75
51.0%
Uppercase Letter 72
49.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 69
92.0%
e 3
 
4.0%
s 3
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
N 69
95.8%
Y 3
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 147
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 69
46.9%
o 69
46.9%
Y 3
 
2.0%
e 3
 
2.0%
s 3
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 147
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 69
46.9%
o 69
46.9%
Y 3
 
2.0%
e 3
 
2.0%
s 3
 
2.0%

qcarincreasea6
Text

MISSING 

Distinct2
Distinct (%)2.8%
Missing928
Missing (%)92.8%
Memory size33.3 KiB
2023-12-09T21:43:38.696209image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.194444444
Min length2

Characters and Unicode

Total characters158
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowYes
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 58
80.6%
yes 14
 
19.4%
2023-12-09T21:43:38.925968image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 58
36.7%
o 58
36.7%
Y 14
 
8.9%
e 14
 
8.9%
s 14
 
8.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 86
54.4%
Uppercase Letter 72
45.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 58
67.4%
e 14
 
16.3%
s 14
 
16.3%
Uppercase Letter
ValueCountFrequency (%)
N 58
80.6%
Y 14
 
19.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 158
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 58
36.7%
o 58
36.7%
Y 14
 
8.9%
e 14
 
8.9%
s 14
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 158
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 58
36.7%
o 58
36.7%
Y 14
 
8.9%
e 14
 
8.9%
s 14
 
8.9%

qcarincreasea7
Text

MISSING 

Distinct2
Distinct (%)2.8%
Missing928
Missing (%)92.8%
Memory size33.3 KiB
2023-12-09T21:43:39.037048image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.083333333
Min length2

Characters and Unicode

Total characters150
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowYes
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 66
91.7%
yes 6
 
8.3%
2023-12-09T21:43:39.264958image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 66
44.0%
o 66
44.0%
Y 6
 
4.0%
e 6
 
4.0%
s 6
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 78
52.0%
Uppercase Letter 72
48.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 66
84.6%
e 6
 
7.7%
s 6
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
N 66
91.7%
Y 6
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 150
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 66
44.0%
o 66
44.0%
Y 6
 
4.0%
e 6
 
4.0%
s 6
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 66
44.0%
o 66
44.0%
Y 6
 
4.0%
e 6
 
4.0%
s 6
 
4.0%

qcarincreasea8
Text

MISSING 

Distinct2
Distinct (%)2.8%
Missing928
Missing (%)92.8%
Memory size33.3 KiB
2023-12-09T21:43:39.376206image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.055555556
Min length2

Characters and Unicode

Total characters148
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 68
94.4%
yes 4
 
5.6%
2023-12-09T21:43:39.613406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 68
45.9%
o 68
45.9%
Y 4
 
2.7%
e 4
 
2.7%
s 4
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 76
51.4%
Uppercase Letter 72
48.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 68
89.5%
e 4
 
5.3%
s 4
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
N 68
94.4%
Y 4
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 148
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 68
45.9%
o 68
45.9%
Y 4
 
2.7%
e 4
 
2.7%
s 4
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 68
45.9%
o 68
45.9%
Y 4
 
2.7%
e 4
 
2.7%
s 4
 
2.7%

qcarincreasea9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)1.4%
Missing928
Missing (%)92.8%
Memory size33.3 KiB
2023-12-09T21:43:39.713925image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters144
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 72
100.0%
2023-12-09T21:43:39.926344image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 72
50.0%
o 72
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 72
50.0%
Lowercase Letter 72
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 72
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 144
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 72
50.0%
o 72
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 144
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 72
50.0%
o 72
50.0%

qelectricconsider
Text

MISSING 

Distinct3
Distinct (%)4.2%
Missing928
Missing (%)92.8%
Memory size36.8 KiB
2023-12-09T21:43:40.103372image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length57
Median length53
Mean length51.48611111
Min length36

Characters and Unicode

Total characters3707
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo, I did not consider buying/leasing an electric car
2nd rowNo, I did not consider buying/leasing an electric car
3rd rowNo, I did not consider buying/leasing an electric car
4th rowNo, I did not consider buying/leasing an electric car
5th rowYes, I considered but I did not buy/lease an electric car
ValueCountFrequency (%)
i 100
15.0%
an 72
10.8%
electric 72
10.8%
car 72
10.8%
did 59
8.9%
not 59
8.9%
yes 41
6.2%
no 31
 
4.7%
consider 31
 
4.7%
buying/leasing 31
 
4.7%
Other values (4) 97
14.6%
2023-12-09T21:43:40.399651image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
593
16.0%
e 385
 
10.4%
c 275
 
7.4%
i 252
 
6.8%
n 252
 
6.8%
d 218
 
5.9%
a 216
 
5.8%
r 203
 
5.5%
t 172
 
4.6%
s 172
 
4.6%
Other values (12) 969
26.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2798
75.5%
Space Separator 593
 
16.0%
Uppercase Letter 172
 
4.6%
Other Punctuation 144
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 385
13.8%
c 275
9.8%
i 252
9.0%
n 252
9.0%
d 218
7.8%
a 216
7.7%
r 203
7.3%
t 172
 
6.1%
s 172
 
6.1%
o 162
 
5.8%
Other values (6) 491
17.5%
Uppercase Letter
ValueCountFrequency (%)
I 100
58.1%
Y 41
23.8%
N 31
 
18.0%
Other Punctuation
ValueCountFrequency (%)
, 72
50.0%
/ 72
50.0%
Space Separator
ValueCountFrequency (%)
593
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2970
80.1%
Common 737
 
19.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 385
13.0%
c 275
9.3%
i 252
 
8.5%
n 252
 
8.5%
d 218
 
7.3%
a 216
 
7.3%
r 203
 
6.8%
t 172
 
5.8%
s 172
 
5.8%
o 162
 
5.5%
Other values (9) 663
22.3%
Common
ValueCountFrequency (%)
593
80.5%
, 72
 
9.8%
/ 72
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3707
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
593
16.0%
e 385
 
10.4%
c 275
 
7.4%
i 252
 
6.8%
n 252
 
6.8%
d 218
 
5.9%
a 216
 
5.8%
r 203
 
5.5%
t 172
 
4.6%
s 172
 
4.6%
Other values (12) 969
26.1%

qnoelectric1
Text

MISSING 

Distinct2
Distinct (%)3.5%
Missing943
Missing (%)94.3%
Memory size32.9 KiB
2023-12-09T21:43:40.522373image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.245614035
Min length2

Characters and Unicode

Total characters128
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 43
75.4%
yes 14
 
24.6%
2023-12-09T21:43:40.751696image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 43
33.6%
o 43
33.6%
Y 14
 
10.9%
e 14
 
10.9%
s 14
 
10.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 71
55.5%
Uppercase Letter 57
44.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 43
60.6%
e 14
 
19.7%
s 14
 
19.7%
Uppercase Letter
ValueCountFrequency (%)
N 43
75.4%
Y 14
 
24.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 128
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 43
33.6%
o 43
33.6%
Y 14
 
10.9%
e 14
 
10.9%
s 14
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 128
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 43
33.6%
o 43
33.6%
Y 14
 
10.9%
e 14
 
10.9%
s 14
 
10.9%

qnoelectric2
Text

MISSING 

Distinct2
Distinct (%)3.5%
Missing943
Missing (%)94.3%
Memory size32.9 KiB
2023-12-09T21:43:40.877362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.350877193
Min length2

Characters and Unicode

Total characters134
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 37
64.9%
yes 20
35.1%
2023-12-09T21:43:41.120239image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 37
27.6%
o 37
27.6%
Y 20
14.9%
e 20
14.9%
s 20
14.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 77
57.5%
Uppercase Letter 57
42.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 37
48.1%
e 20
26.0%
s 20
26.0%
Uppercase Letter
ValueCountFrequency (%)
N 37
64.9%
Y 20
35.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 134
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 37
27.6%
o 37
27.6%
Y 20
14.9%
e 20
14.9%
s 20
14.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 37
27.6%
o 37
27.6%
Y 20
14.9%
e 20
14.9%
s 20
14.9%

qnoelectric3
Text

MISSING 

Distinct2
Distinct (%)3.5%
Missing943
Missing (%)94.3%
Memory size32.9 KiB
2023-12-09T21:43:41.229588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.035087719
Min length2

Characters and Unicode

Total characters116
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 55
96.5%
yes 2
 
3.5%
2023-12-09T21:43:41.451291image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 55
47.4%
o 55
47.4%
Y 2
 
1.7%
e 2
 
1.7%
s 2
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 59
50.9%
Uppercase Letter 57
49.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 55
93.2%
e 2
 
3.4%
s 2
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
N 55
96.5%
Y 2
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 116
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 55
47.4%
o 55
47.4%
Y 2
 
1.7%
e 2
 
1.7%
s 2
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 116
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 55
47.4%
o 55
47.4%
Y 2
 
1.7%
e 2
 
1.7%
s 2
 
1.7%

qnoelectric4
Text

MISSING 

Distinct2
Distinct (%)3.5%
Missing943
Missing (%)94.3%
Memory size32.9 KiB
2023-12-09T21:43:41.564225image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.157894737
Min length2

Characters and Unicode

Total characters123
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 48
84.2%
yes 9
 
15.8%
2023-12-09T21:43:41.788429image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 48
39.0%
o 48
39.0%
Y 9
 
7.3%
e 9
 
7.3%
s 9
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 66
53.7%
Uppercase Letter 57
46.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 48
72.7%
e 9
 
13.6%
s 9
 
13.6%
Uppercase Letter
ValueCountFrequency (%)
N 48
84.2%
Y 9
 
15.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 123
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 48
39.0%
o 48
39.0%
Y 9
 
7.3%
e 9
 
7.3%
s 9
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 48
39.0%
o 48
39.0%
Y 9
 
7.3%
e 9
 
7.3%
s 9
 
7.3%

qnoelectric5
Text

MISSING 

Distinct2
Distinct (%)3.5%
Missing943
Missing (%)94.3%
Memory size32.9 KiB
2023-12-09T21:43:41.898218image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.070175439
Min length2

Characters and Unicode

Total characters118
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 53
93.0%
yes 4
 
7.0%
2023-12-09T21:43:42.123080image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 53
44.9%
o 53
44.9%
Y 4
 
3.4%
e 4
 
3.4%
s 4
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 61
51.7%
Uppercase Letter 57
48.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 53
86.9%
e 4
 
6.6%
s 4
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
N 53
93.0%
Y 4
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 118
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 53
44.9%
o 53
44.9%
Y 4
 
3.4%
e 4
 
3.4%
s 4
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 53
44.9%
o 53
44.9%
Y 4
 
3.4%
e 4
 
3.4%
s 4
 
3.4%

qnoelectric6
Text

MISSING 

Distinct2
Distinct (%)3.5%
Missing943
Missing (%)94.3%
Memory size32.9 KiB
2023-12-09T21:43:42.235953image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.087719298
Min length2

Characters and Unicode

Total characters119
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 52
91.2%
yes 5
 
8.8%
2023-12-09T21:43:42.460989image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 52
43.7%
o 52
43.7%
Y 5
 
4.2%
e 5
 
4.2%
s 5
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 62
52.1%
Uppercase Letter 57
47.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 52
83.9%
e 5
 
8.1%
s 5
 
8.1%
Uppercase Letter
ValueCountFrequency (%)
N 52
91.2%
Y 5
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 119
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 52
43.7%
o 52
43.7%
Y 5
 
4.2%
e 5
 
4.2%
s 5
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 119
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 52
43.7%
o 52
43.7%
Y 5
 
4.2%
e 5
 
4.2%
s 5
 
4.2%

qnoelectric7
Text

MISSING 

Distinct2
Distinct (%)3.5%
Missing943
Missing (%)94.3%
Memory size32.9 KiB
2023-12-09T21:43:42.573711image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.052631579
Min length2

Characters and Unicode

Total characters117
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 54
94.7%
yes 3
 
5.3%
2023-12-09T21:43:42.797350image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 54
46.2%
o 54
46.2%
Y 3
 
2.6%
e 3
 
2.6%
s 3
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 60
51.3%
Uppercase Letter 57
48.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 54
90.0%
e 3
 
5.0%
s 3
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
N 54
94.7%
Y 3
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 117
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 54
46.2%
o 54
46.2%
Y 3
 
2.6%
e 3
 
2.6%
s 3
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 117
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 54
46.2%
o 54
46.2%
Y 3
 
2.6%
e 3
 
2.6%
s 3
 
2.6%

qnoelectric8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)1.8%
Missing943
Missing (%)94.3%
Memory size32.9 KiB
2023-12-09T21:43:42.898903image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters114
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 57
100.0%
2023-12-09T21:43:43.103647image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 57
50.0%
o 57
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 57
50.0%
Lowercase Letter 57
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 57
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 114
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 57
50.0%
o 57
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 114
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 57
50.0%
o 57
50.0%

gcarpark1_qcarpark1_ma
Text

MISSING 

Distinct7
Distinct (%)1.2%
Missing403
Missing (%)40.3%
Memory size62.2 KiB
2023-12-09T21:43:43.300692image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length42
Mean length27.95477387
Min length5

Characters and Unicode

Total characters16689
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowIn a single family home garage or driveway
2nd rowIn another parking garage or lot
3rd rowIn a single family home garage or driveway
4th rowIn a single family home garage or driveway
5th rowIn a single family home garage or driveway
ValueCountFrequency (%)
in 414
12.4%
garage 307
9.2%
or 307
9.2%
a 299
8.9%
on 256
 
7.6%
street 256
 
7.6%
the 256
 
7.6%
driveway 219
 
6.5%
home 192
 
5.7%
family 192
 
5.7%
Other values (10) 651
19.4%
2023-12-09T21:43:43.639599image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2752
16.5%
e 1828
11.0%
a 1581
9.5%
r 1352
 
8.1%
n 1092
 
6.5%
t 1084
 
6.5%
g 921
 
5.5%
i 878
 
5.3%
o 729
 
4.4%
l 579
 
3.5%
Other values (15) 3893
23.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13340
79.9%
Space Separator 2752
 
16.5%
Uppercase Letter 597
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1828
13.7%
a 1581
11.9%
r 1352
10.1%
n 1092
 
8.2%
t 1084
 
8.1%
g 921
 
6.9%
i 878
 
6.6%
o 729
 
5.5%
l 579
 
4.3%
h 516
 
3.9%
Other values (11) 2780
20.8%
Uppercase Letter
ValueCountFrequency (%)
I 334
55.9%
O 262
43.9%
R 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2752
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13937
83.5%
Common 2752
 
16.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1828
13.1%
a 1581
11.3%
r 1352
9.7%
n 1092
 
7.8%
t 1084
 
7.8%
g 921
 
6.6%
i 878
 
6.3%
o 729
 
5.2%
l 579
 
4.2%
h 516
 
3.7%
Other values (14) 3377
24.2%
Common
ValueCountFrequency (%)
2752
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16689
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2752
16.5%
e 1828
11.0%
a 1581
9.5%
r 1352
 
8.1%
n 1092
 
6.5%
t 1084
 
6.5%
g 921
 
5.5%
i 878
 
5.3%
o 729
 
4.4%
l 579
 
3.5%
Other values (15) 3893
23.3%

gcarpark1_qcarpark2_ma
Text

MISSING 

Distinct6
Distinct (%)3.2%
Missing814
Missing (%)81.4%
Memory size41.1 KiB
2023-12-09T21:43:43.850674image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length42
Mean length28.60752688
Min length5

Characters and Unicode

Total characters5321
Distinct characters24
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIn a single family home garage or driveway
2nd rowOn the street
3rd rowIn a single family home garage or driveway
4th rowOther
5th rowIn a single family home garage or driveway
ValueCountFrequency (%)
in 123
11.6%
a 106
10.0%
garage 98
9.3%
or 98
9.3%
driveway 94
8.9%
single 81
7.6%
family 81
7.6%
home 81
7.6%
street 73
6.9%
the 73
6.9%
Other values (9) 151
14.3%
2023-12-09T21:43:44.205396image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
873
16.4%
e 605
11.4%
a 524
 
9.8%
r 412
 
7.7%
n 311
 
5.8%
i 297
 
5.6%
g 294
 
5.5%
t 267
 
5.0%
o 213
 
4.0%
l 191
 
3.6%
Other values (14) 1334
25.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4262
80.1%
Space Separator 873
 
16.4%
Uppercase Letter 186
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 605
14.2%
a 524
12.3%
r 412
9.7%
n 311
 
7.3%
i 297
 
7.0%
g 294
 
6.9%
t 267
 
6.3%
o 213
 
5.0%
l 191
 
4.5%
y 187
 
4.4%
Other values (11) 961
22.5%
Uppercase Letter
ValueCountFrequency (%)
I 111
59.7%
O 75
40.3%
Space Separator
ValueCountFrequency (%)
873
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4448
83.6%
Common 873
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 605
13.6%
a 524
11.8%
r 412
 
9.3%
n 311
 
7.0%
i 297
 
6.7%
g 294
 
6.6%
t 267
 
6.0%
o 213
 
4.8%
l 191
 
4.3%
y 187
 
4.2%
Other values (13) 1147
25.8%
Common
ValueCountFrequency (%)
873
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5321
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
873
16.4%
e 605
11.4%
a 524
 
9.8%
r 412
 
7.7%
n 311
 
5.8%
i 297
 
5.6%
g 294
 
5.5%
t 267
 
5.0%
o 213
 
4.0%
l 191
 
3.6%
Other values (14) 1334
25.1%

gcarpark1_qcarpark3_ma
Text

MISSING 

Distinct5
Distinct (%)13.2%
Missing962
Missing (%)96.2%
Memory size33.2 KiB
2023-12-09T21:43:44.420230image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length13
Mean length24.23684211
Min length13

Characters and Unicode

Total characters921
Distinct characters24
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)5.3%

Sample

1st rowIn a single family home garage or driveway
2nd rowOn the street
3rd rowIn a single family home garage or driveway
4th rowIn a single family home garage or driveway
5th rowOn the street
ValueCountFrequency (%)
on 20
10.7%
street 20
10.7%
the 20
10.7%
in 19
10.2%
a 17
9.1%
driveway 16
8.6%
garage 14
7.5%
or 14
7.5%
home 12
6.4%
family 12
6.4%
Other values (8) 23
12.3%
2023-12-09T21:43:44.748460image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
149
16.2%
e 120
13.0%
a 81
 
8.8%
r 72
 
7.8%
t 65
 
7.1%
n 55
 
6.0%
i 44
 
4.8%
g 42
 
4.6%
h 37
 
4.0%
s 36
 
3.9%
Other values (14) 220
23.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 734
79.7%
Space Separator 149
 
16.2%
Uppercase Letter 38
 
4.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 120
16.3%
a 81
11.0%
r 72
9.8%
t 65
8.9%
n 55
 
7.5%
i 44
 
6.0%
g 42
 
5.7%
h 37
 
5.0%
s 36
 
4.9%
o 30
 
4.1%
Other values (11) 152
20.7%
Uppercase Letter
ValueCountFrequency (%)
O 20
52.6%
I 18
47.4%
Space Separator
ValueCountFrequency (%)
149
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 772
83.8%
Common 149
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 120
15.5%
a 81
10.5%
r 72
 
9.3%
t 65
 
8.4%
n 55
 
7.1%
i 44
 
5.7%
g 42
 
5.4%
h 37
 
4.8%
s 36
 
4.7%
o 30
 
3.9%
Other values (13) 190
24.6%
Common
ValueCountFrequency (%)
149
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 921
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
149
16.2%
e 120
13.0%
a 81
 
8.8%
r 72
 
7.8%
t 65
 
7.1%
n 55
 
6.0%
i 44
 
4.8%
g 42
 
4.6%
h 37
 
4.0%
s 36
 
3.9%
Other values (14) 220
23.9%

gcarpark1_qcarpark4_ma
Text

MISSING 

Distinct3
Distinct (%)25.0%
Missing988
Missing (%)98.8%
Memory size31.9 KiB
2023-12-09T21:43:44.951031image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length13
Mean length21.83333333
Min length13

Characters and Unicode

Total characters262
Distinct characters22
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)8.3%

Sample

1st rowIn a single family home garage or driveway
2nd rowOn the street
3rd rowIn a single family home garage or driveway
4th rowIn another parking garage or lot
5th rowOn the street
ValueCountFrequency (%)
on 8
14.8%
the 8
14.8%
street 8
14.8%
in 4
7.4%
garage 4
7.4%
or 4
7.4%
a 3
 
5.6%
single 3
 
5.6%
family 3
 
5.6%
home 3
 
5.6%
Other values (4) 6
11.1%
2023-12-09T21:43:45.268588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
16.0%
e 38
14.5%
t 26
9.9%
r 21
 
8.0%
a 19
 
7.3%
n 17
 
6.5%
g 12
 
4.6%
h 12
 
4.6%
s 11
 
4.2%
i 10
 
3.8%
Other values (12) 54
20.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 208
79.4%
Space Separator 42
 
16.0%
Uppercase Letter 12
 
4.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 38
18.3%
t 26
12.5%
r 21
10.1%
a 19
9.1%
n 17
8.2%
g 12
 
5.8%
h 12
 
5.8%
s 11
 
5.3%
i 10
 
4.8%
o 9
 
4.3%
Other values (9) 33
15.9%
Uppercase Letter
ValueCountFrequency (%)
O 8
66.7%
I 4
33.3%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 220
84.0%
Common 42
 
16.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 38
17.3%
t 26
11.8%
r 21
9.5%
a 19
8.6%
n 17
 
7.7%
g 12
 
5.5%
h 12
 
5.5%
s 11
 
5.0%
i 10
 
4.5%
o 9
 
4.1%
Other values (11) 45
20.5%
Common
ValueCountFrequency (%)
42
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 262
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
16.0%
e 38
14.5%
t 26
9.9%
r 21
 
8.0%
a 19
 
7.3%
n 17
 
6.5%
g 12
 
4.6%
h 12
 
4.6%
s 11
 
4.2%
i 10
 
3.8%
Other values (12) 54
20.6%

qpaytopark
Text

MISSING 

Distinct2
Distinct (%)1.7%
Missing883
Missing (%)88.3%
Memory size34.5 KiB
2023-12-09T21:43:45.391548image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.64957265
Min length2

Characters and Unicode

Total characters310
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowNo
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 76
65.0%
no 41
35.0%
2023-12-09T21:43:45.630980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 76
24.5%
e 76
24.5%
s 76
24.5%
N 41
13.2%
o 41
13.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 193
62.3%
Uppercase Letter 117
37.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 76
39.4%
s 76
39.4%
o 41
21.2%
Uppercase Letter
ValueCountFrequency (%)
Y 76
65.0%
N 41
35.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 310
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 76
24.5%
e 76
24.5%
s 76
24.5%
N 41
13.2%
o 41
13.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 76
24.5%
e 76
24.5%
s 76
24.5%
N 41
13.2%
o 41
13.2%

qpaytopark_amount
Text

MISSING 

Distinct44
Distinct (%)60.3%
Missing927
Missing (%)92.7%
Memory size33.3 KiB
2023-12-09T21:43:45.866531image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.657534247
Min length1

Characters and Unicode

Total characters194
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)39.7%

Sample

1st row120
2nd row60
3rd row175
4th row125
5th row60
ValueCountFrequency (%)
60 7
 
9.6%
150 4
 
5.5%
200 4
 
5.5%
400 4
 
5.5%
120 3
 
4.1%
20 3
 
4.1%
125 3
 
4.1%
300 2
 
2.7%
600 2
 
2.7%
175 2
 
2.7%
Other values (34) 39
53.4%
2023-12-09T21:43:46.238137image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 64
33.0%
5 29
14.9%
2 26
13.4%
1 22
 
11.3%
6 14
 
7.2%
4 14
 
7.2%
3 12
 
6.2%
7 8
 
4.1%
9 3
 
1.5%
8 2
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 194
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 64
33.0%
5 29
14.9%
2 26
13.4%
1 22
 
11.3%
6 14
 
7.2%
4 14
 
7.2%
3 12
 
6.2%
7 8
 
4.1%
9 3
 
1.5%
8 2
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 194
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 64
33.0%
5 29
14.9%
2 26
13.4%
1 22
 
11.3%
6 14
 
7.2%
4 14
 
7.2%
3 12
 
6.2%
7 8
 
4.1%
9 3
 
1.5%
8 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 194
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 64
33.0%
5 29
14.9%
2 26
13.4%
1 22
 
11.3%
6 14
 
7.2%
4 14
 
7.2%
3 12
 
6.2%
7 8
 
4.1%
9 3
 
1.5%
8 2
 
1.0%

qshare1
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.8 KiB
2023-12-09T21:43:46.366325image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.073146293
Min length2

Characters and Unicode

Total characters2069
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowYes
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 925
92.7%
yes 73
 
7.3%
2023-12-09T21:43:46.589168image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 925
44.7%
o 925
44.7%
Y 73
 
3.5%
e 73
 
3.5%
s 73
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1071
51.8%
Uppercase Letter 998
48.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 925
86.4%
e 73
 
6.8%
s 73
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
N 925
92.7%
Y 73
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 2069
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 925
44.7%
o 925
44.7%
Y 73
 
3.5%
e 73
 
3.5%
s 73
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2069
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 925
44.7%
o 925
44.7%
Y 73
 
3.5%
e 73
 
3.5%
s 73
 
3.5%

qshare2
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:43:46.699824image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.033066132
Min length2

Characters and Unicode

Total characters2029
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 965
96.7%
yes 33
 
3.3%
2023-12-09T21:43:46.925251image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 965
47.6%
o 965
47.6%
Y 33
 
1.6%
e 33
 
1.6%
s 33
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1031
50.8%
Uppercase Letter 998
49.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 965
93.6%
e 33
 
3.2%
s 33
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
N 965
96.7%
Y 33
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 2029
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 965
47.6%
o 965
47.6%
Y 33
 
1.6%
e 33
 
1.6%
s 33
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2029
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 965
47.6%
o 965
47.6%
Y 33
 
1.6%
e 33
 
1.6%
s 33
 
1.6%

qshare3
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.8 KiB
2023-12-09T21:43:47.037830image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.071142285
Min length2

Characters and Unicode

Total characters2067
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 927
92.9%
yes 71
 
7.1%
2023-12-09T21:43:47.260104image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 927
44.8%
o 927
44.8%
Y 71
 
3.4%
e 71
 
3.4%
s 71
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1069
51.7%
Uppercase Letter 998
48.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 927
86.7%
e 71
 
6.6%
s 71
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
N 927
92.9%
Y 71
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 2067
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 927
44.8%
o 927
44.8%
Y 71
 
3.4%
e 71
 
3.4%
s 71
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 927
44.8%
o 927
44.8%
Y 71
 
3.4%
e 71
 
3.4%
s 71
 
3.4%

qshare4
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:43:47.368882image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.002004008
Min length2

Characters and Unicode

Total characters1998
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 996
99.8%
yes 2
 
0.2%
2023-12-09T21:43:47.589351image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 996
49.8%
o 996
49.8%
Y 2
 
0.1%
e 2
 
0.1%
s 2
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1000
50.1%
Uppercase Letter 998
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 996
99.6%
e 2
 
0.2%
s 2
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 996
99.8%
Y 2
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 1998
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 996
49.8%
o 996
49.8%
Y 2
 
0.1%
e 2
 
0.1%
s 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1998
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 996
49.8%
o 996
49.8%
Y 2
 
0.1%
e 2
 
0.1%
s 2
 
0.1%

qshare5
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:43:48.155589image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.02004008
Min length2

Characters and Unicode

Total characters2016
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 978
98.0%
yes 20
 
2.0%
2023-12-09T21:43:48.382738image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 978
48.5%
o 978
48.5%
Y 20
 
1.0%
e 20
 
1.0%
s 20
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1018
50.5%
Uppercase Letter 998
49.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 978
96.1%
e 20
 
2.0%
s 20
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
N 978
98.0%
Y 20
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2016
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 978
48.5%
o 978
48.5%
Y 20
 
1.0%
e 20
 
1.0%
s 20
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 978
48.5%
o 978
48.5%
Y 20
 
1.0%
e 20
 
1.0%
s 20
 
1.0%

qshare6
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size58.5 KiB
2023-12-09T21:43:48.504311image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.816633267
Min length2

Characters and Unicode

Total characters2811
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 815
81.7%
no 183
 
18.3%
2023-12-09T21:43:48.734865image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 815
29.0%
e 815
29.0%
s 815
29.0%
N 183
 
6.5%
o 183
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1813
64.5%
Uppercase Letter 998
35.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 815
45.0%
s 815
45.0%
o 183
 
10.1%
Uppercase Letter
ValueCountFrequency (%)
Y 815
81.7%
N 183
 
18.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 2811
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 815
29.0%
e 815
29.0%
s 815
29.0%
N 183
 
6.5%
o 183
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2811
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 815
29.0%
e 815
29.0%
s 815
29.0%
N 183
 
6.5%
o 183
 
6.5%

qshare7
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:43:48.844157image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.018036072
Min length2

Characters and Unicode

Total characters2014
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 980
98.2%
yes 18
 
1.8%
2023-12-09T21:43:49.068602image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 980
48.7%
o 980
48.7%
Y 18
 
0.9%
e 18
 
0.9%
s 18
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1016
50.4%
Uppercase Letter 998
49.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 980
96.5%
e 18
 
1.8%
s 18
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
N 980
98.2%
Y 18
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 2014
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 980
48.7%
o 980
48.7%
Y 18
 
0.9%
e 18
 
0.9%
s 18
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2014
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 980
48.7%
o 980
48.7%
Y 18
 
0.9%
e 18
 
0.9%
s 18
 
0.9%

qshare8
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:43:49.174119image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1996
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 998
100.0%
2023-12-09T21:43:49.387256image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 998
50.0%
o 998
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 998
50.0%
Lowercase Letter 998
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 998
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 998
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1996
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 998
50.0%
o 998
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1996
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 998
50.0%
o 998
50.0%

qsmartphone
Text

Distinct2
Distinct (%)0.2%
Missing6
Missing (%)0.6%
Memory size58.4 KiB
2023-12-09T21:43:49.505200image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.881287726
Min length2

Characters and Unicode

Total characters2864
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 876
88.1%
no 118
 
11.9%
2023-12-09T21:43:49.739165image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 876
30.6%
e 876
30.6%
s 876
30.6%
N 118
 
4.1%
o 118
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1870
65.3%
Uppercase Letter 994
34.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 876
46.8%
s 876
46.8%
o 118
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
Y 876
88.1%
N 118
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 2864
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 876
30.6%
e 876
30.6%
s 876
30.6%
N 118
 
4.1%
o 118
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2864
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 876
30.6%
e 876
30.6%
s 876
30.6%
N 118
 
4.1%
o 118
 
4.1%

qtripplanapp
Text

MISSING 

Distinct8
Distinct (%)0.9%
Missing106
Missing (%)10.6%
Memory size67.8 KiB
2023-12-09T21:43:49.900238image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length28
Median length20
Mean length16.74161074
Min length5

Characters and Unicode

Total characters14967
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDaily
2nd rowOnce a week
3rd rowA few times a month
4th rowA few times a year
5th rowSeveral times a week
ValueCountFrequency (%)
a 1130
31.2%
times 581
16.1%
few 382
 
10.6%
week 301
 
8.3%
month 224
 
6.2%
year 223
 
6.2%
several 199
 
5.5%
once 167
 
4.6%
daily 146
 
4.0%
less 132
 
3.6%
2023-12-09T21:43:50.188186image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2723
18.2%
e 2485
16.6%
a 1558
10.4%
t 937
 
6.3%
s 845
 
5.6%
m 805
 
5.4%
i 727
 
4.9%
w 683
 
4.6%
n 523
 
3.5%
r 422
 
2.8%
Other values (13) 3259
21.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11350
75.8%
Space Separator 2723
 
18.2%
Uppercase Letter 894
 
6.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2485
21.9%
a 1558
13.7%
t 937
 
8.3%
s 845
 
7.4%
m 805
 
7.1%
i 727
 
6.4%
w 683
 
6.0%
n 523
 
4.6%
r 422
 
3.7%
f 382
 
3.4%
Other values (7) 1983
17.5%
Uppercase Letter
ValueCountFrequency (%)
A 272
30.4%
S 199
22.3%
D 146
16.3%
O 145
16.2%
L 132
14.8%
Space Separator
ValueCountFrequency (%)
2723
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12244
81.8%
Common 2723
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2485
20.3%
a 1558
12.7%
t 937
 
7.7%
s 845
 
6.9%
m 805
 
6.6%
i 727
 
5.9%
w 683
 
5.6%
n 523
 
4.3%
r 422
 
3.4%
f 382
 
3.1%
Other values (12) 2877
23.5%
Common
ValueCountFrequency (%)
2723
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14967
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2723
18.2%
e 2485
16.6%
a 1558
10.4%
t 937
 
6.3%
s 845
 
5.6%
m 805
 
5.4%
i 727
 
4.9%
w 683
 
4.6%
n 523
 
3.5%
r 422
 
2.8%
Other values (13) 3259
21.8%

qridehail1
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing647
Missing (%)64.7%
Memory size40.8 KiB
2023-12-09T21:43:50.339613image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.458923513
Min length2

Characters and Unicode

Total characters868
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 191
54.1%
yes 162
45.9%
2023-12-09T21:43:50.586290image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 191
22.0%
o 191
22.0%
Y 162
18.7%
e 162
18.7%
s 162
18.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 515
59.3%
Uppercase Letter 353
40.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 191
37.1%
e 162
31.5%
s 162
31.5%
Uppercase Letter
ValueCountFrequency (%)
N 191
54.1%
Y 162
45.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 868
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 191
22.0%
o 191
22.0%
Y 162
18.7%
e 162
18.7%
s 162
18.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 868
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 191
22.0%
o 191
22.0%
Y 162
18.7%
e 162
18.7%
s 162
18.7%

qridehail2
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing647
Missing (%)64.7%
Memory size40.8 KiB
2023-12-09T21:43:50.706404image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.235127479
Min length2

Characters and Unicode

Total characters789
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 270
76.5%
yes 83
 
23.5%
2023-12-09T21:43:50.939216image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 270
34.2%
o 270
34.2%
Y 83
 
10.5%
e 83
 
10.5%
s 83
 
10.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 436
55.3%
Uppercase Letter 353
44.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 270
61.9%
e 83
 
19.0%
s 83
 
19.0%
Uppercase Letter
ValueCountFrequency (%)
N 270
76.5%
Y 83
 
23.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 789
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 270
34.2%
o 270
34.2%
Y 83
 
10.5%
e 83
 
10.5%
s 83
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 789
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 270
34.2%
o 270
34.2%
Y 83
 
10.5%
e 83
 
10.5%
s 83
 
10.5%

qridehail3
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing647
Missing (%)64.7%
Memory size40.7 KiB
2023-12-09T21:43:51.049515image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.076487252
Min length2

Characters and Unicode

Total characters733
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 326
92.4%
yes 27
 
7.6%
2023-12-09T21:43:51.279172image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 326
44.5%
o 326
44.5%
Y 27
 
3.7%
e 27
 
3.7%
s 27
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 380
51.8%
Uppercase Letter 353
48.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 326
85.8%
e 27
 
7.1%
s 27
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
N 326
92.4%
Y 27
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 733
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 326
44.5%
o 326
44.5%
Y 27
 
3.7%
e 27
 
3.7%
s 27
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 733
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 326
44.5%
o 326
44.5%
Y 27
 
3.7%
e 27
 
3.7%
s 27
 
3.7%

qridehail4
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing647
Missing (%)64.7%
Memory size40.7 KiB
2023-12-09T21:43:51.394346image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.04815864
Min length2

Characters and Unicode

Total characters723
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 336
95.2%
yes 17
 
4.8%
2023-12-09T21:43:51.635062image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 336
46.5%
o 336
46.5%
Y 17
 
2.4%
e 17
 
2.4%
s 17
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 370
51.2%
Uppercase Letter 353
48.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 336
90.8%
e 17
 
4.6%
s 17
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
N 336
95.2%
Y 17
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 723
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 336
46.5%
o 336
46.5%
Y 17
 
2.4%
e 17
 
2.4%
s 17
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 723
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 336
46.5%
o 336
46.5%
Y 17
 
2.4%
e 17
 
2.4%
s 17
 
2.4%

qridehail5
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing647
Missing (%)64.7%
Memory size40.7 KiB
2023-12-09T21:43:51.747432image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.014164306
Min length2

Characters and Unicode

Total characters711
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 348
98.6%
yes 5
 
1.4%
2023-12-09T21:43:51.982432image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 348
48.9%
o 348
48.9%
Y 5
 
0.7%
e 5
 
0.7%
s 5
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 358
50.4%
Uppercase Letter 353
49.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 348
97.2%
e 5
 
1.4%
s 5
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
N 348
98.6%
Y 5
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 711
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 348
48.9%
o 348
48.9%
Y 5
 
0.7%
e 5
 
0.7%
s 5
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 711
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 348
48.9%
o 348
48.9%
Y 5
 
0.7%
e 5
 
0.7%
s 5
 
0.7%

qridehail6
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing647
Missing (%)64.7%
Memory size40.8 KiB
2023-12-09T21:43:52.120559image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.470254958
Min length2

Characters and Unicode

Total characters872
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 187
53.0%
yes 166
47.0%
2023-12-09T21:43:52.385871image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 187
21.4%
o 187
21.4%
Y 166
19.0%
e 166
19.0%
s 166
19.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 519
59.5%
Uppercase Letter 353
40.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 187
36.0%
e 166
32.0%
s 166
32.0%
Uppercase Letter
ValueCountFrequency (%)
N 187
53.0%
Y 166
47.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 872
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 187
21.4%
o 187
21.4%
Y 166
19.0%
e 166
19.0%
s 166
19.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 187
21.4%
o 187
21.4%
Y 166
19.0%
e 166
19.0%
s 166
19.0%

qridehail7
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing647
Missing (%)64.7%
Memory size40.7 KiB
2023-12-09T21:43:52.496860image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.002832861
Min length2

Characters and Unicode

Total characters707
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 352
99.7%
yes 1
 
0.3%
2023-12-09T21:43:52.723216image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 352
49.8%
o 352
49.8%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 354
50.1%
Uppercase Letter 353
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 352
99.4%
e 1
 
0.3%
s 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 352
99.7%
Y 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 707
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 352
49.8%
o 352
49.8%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 707
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 352
49.8%
o 352
49.8%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

qridehail8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing647
Missing (%)64.7%
Memory size40.7 KiB
2023-12-09T21:43:52.827034image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters706
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 353
100.0%
2023-12-09T21:43:53.043028image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 353
50.0%
o 353
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 353
50.0%
Lowercase Letter 353
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 353
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 353
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 706
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 353
50.0%
o 353
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 706
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 353
50.0%
o 353
50.0%

qridehail_freq
Text

MISSING 

Distinct7
Distinct (%)3.8%
Missing814
Missing (%)81.4%
Memory size39.2 KiB
2023-12-09T21:43:53.199913image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length28
Median length19
Mean length18.27956989
Min length5

Characters and Unicode

Total characters3400
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSeveral times a week
2nd rowA few times a year
3rd rowA few times a year
4th rowOnce a week
5th rowOnce a month
ValueCountFrequency (%)
a 295
34.5%
times 144
16.9%
few 112
 
13.1%
month 70
 
8.2%
year 63
 
7.4%
week 50
 
5.9%
once 39
 
4.6%
several 32
 
3.7%
less 23
 
2.7%
than 23
 
2.7%
2023-12-09T21:43:53.479426image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
668
19.6%
e 545
16.0%
a 327
9.6%
t 237
 
7.0%
m 214
 
6.3%
s 190
 
5.6%
w 162
 
4.8%
i 147
 
4.3%
n 132
 
3.9%
f 112
 
3.3%
Other values (13) 666
19.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2546
74.9%
Space Separator 668
 
19.6%
Uppercase Letter 186
 
5.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 545
21.4%
a 327
12.8%
t 237
9.3%
m 214
 
8.4%
s 190
 
7.5%
w 162
 
6.4%
i 147
 
5.8%
n 132
 
5.2%
f 112
 
4.4%
r 95
 
3.7%
Other values (7) 385
15.1%
Uppercase Letter
ValueCountFrequency (%)
A 89
47.8%
O 39
21.0%
S 32
 
17.2%
L 23
 
12.4%
D 3
 
1.6%
Space Separator
ValueCountFrequency (%)
668
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2732
80.4%
Common 668
 
19.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 545
19.9%
a 327
12.0%
t 237
8.7%
m 214
 
7.8%
s 190
 
7.0%
w 162
 
5.9%
i 147
 
5.4%
n 132
 
4.8%
f 112
 
4.1%
r 95
 
3.5%
Other values (12) 571
20.9%
Common
ValueCountFrequency (%)
668
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
668
19.6%
e 545
16.0%
a 327
9.6%
t 237
 
7.0%
m 214
 
6.3%
s 190
 
5.6%
w 162
 
4.8%
i 147
 
4.3%
n 132
 
3.9%
f 112
 
3.3%
Other values (13) 666
19.6%

qridehailpurpose
Text

MISSING 

Distinct9
Distinct (%)4.9%
Missing815
Missing (%)81.5%
Memory size38.6 KiB
2023-12-09T21:43:53.680277image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length31
Median length17
Mean length14.87567568
Min length5

Characters and Unicode

Total characters2752
Distinct characters32
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBusiness
2nd rowOther
3rd rowSocial/recreation
4th rowPersonal errands
5th rowOther
ValueCountFrequency (%)
social/recreation 60
20.0%
personal 32
10.7%
errands 32
10.7%
commute 22
 
7.3%
to/from 22
 
7.3%
work 22
 
7.3%
other 21
 
7.0%
business 19
 
6.3%
medical 13
 
4.3%
visit 13
 
4.3%
Other values (5) 44
14.7%
2023-12-09T21:43:54.009068image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 294
 
10.7%
o 289
 
10.5%
e 272
 
9.9%
i 217
 
7.9%
a 197
 
7.2%
n 169
 
6.1%
c 161
 
5.9%
t 151
 
5.5%
s 147
 
5.3%
115
 
4.2%
Other values (22) 740
26.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2331
84.7%
Uppercase Letter 185
 
6.7%
Space Separator 115
 
4.2%
Other Punctuation 95
 
3.5%
Open Punctuation 13
 
0.5%
Close Punctuation 13
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 294
12.6%
o 289
12.4%
e 272
11.7%
i 217
9.3%
a 197
8.5%
n 169
7.3%
c 161
6.9%
t 151
6.5%
s 147
6.3%
l 107
 
4.6%
Other values (10) 327
14.0%
Uppercase Letter
ValueCountFrequency (%)
S 68
36.8%
P 32
17.3%
C 22
 
11.9%
O 21
 
11.4%
B 19
 
10.3%
M 13
 
7.0%
D 10
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/ 82
86.3%
' 13
 
13.7%
Space Separator
ValueCountFrequency (%)
115
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2516
91.4%
Common 236
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 294
11.7%
o 289
11.5%
e 272
10.8%
i 217
8.6%
a 197
 
7.8%
n 169
 
6.7%
c 161
 
6.4%
t 151
 
6.0%
s 147
 
5.8%
l 107
 
4.3%
Other values (17) 512
20.3%
Common
ValueCountFrequency (%)
115
48.7%
/ 82
34.7%
( 13
 
5.5%
' 13
 
5.5%
) 13
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2752
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 294
 
10.7%
o 289
 
10.5%
e 272
 
9.9%
i 217
 
7.9%
a 197
 
7.2%
n 169
 
6.1%
c 161
 
5.9%
t 151
 
5.5%
s 147
 
5.3%
115
 
4.2%
Other values (22) 740
26.9%

qbikeown
Text

Distinct2
Distinct (%)0.2%
Missing7
Missing (%)0.7%
Memory size57.9 KiB
2023-12-09T21:43:54.136800image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.342396777
Min length2

Characters and Unicode

Total characters2326
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 653
65.8%
yes 340
34.2%
2023-12-09T21:43:54.387324image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 653
28.1%
o 653
28.1%
Y 340
14.6%
e 340
14.6%
s 340
14.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1333
57.3%
Uppercase Letter 993
42.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 653
49.0%
e 340
25.5%
s 340
25.5%
Uppercase Letter
ValueCountFrequency (%)
N 653
65.8%
Y 340
34.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 2326
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 653
28.1%
o 653
28.1%
Y 340
14.6%
e 340
14.6%
s 340
14.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2326
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 653
28.1%
o 653
28.1%
Y 340
14.6%
e 340
14.6%
s 340
14.6%

qbikemany
Text

MISSING 

Distinct8
Distinct (%)2.4%
Missing664
Missing (%)66.4%
Memory size39.9 KiB
2023-12-09T21:43:54.502716image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters336
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row2
2nd row2
3rd row2
4th row1
5th row1
ValueCountFrequency (%)
1 157
46.7%
2 109
32.4%
3 37
 
11.0%
4 24
 
7.1%
5 3
 
0.9%
6 3
 
0.9%
8 2
 
0.6%
7 1
 
0.3%
2023-12-09T21:43:54.729449image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 157
46.7%
2 109
32.4%
3 37
 
11.0%
4 24
 
7.1%
5 3
 
0.9%
6 3
 
0.9%
8 2
 
0.6%
7 1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 336
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 157
46.7%
2 109
32.4%
3 37
 
11.0%
4 24
 
7.1%
5 3
 
0.9%
6 3
 
0.9%
8 2
 
0.6%
7 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 157
46.7%
2 109
32.4%
3 37
 
11.0%
4 24
 
7.1%
5 3
 
0.9%
6 3
 
0.9%
8 2
 
0.6%
7 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 157
46.7%
2 109
32.4%
3 37
 
11.0%
4 24
 
7.1%
5 3
 
0.9%
6 3
 
0.9%
8 2
 
0.6%
7 1
 
0.3%

qbiketype1
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing664
Missing (%)66.4%
Memory size40.6 KiB
2023-12-09T21:43:54.851135image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.973214286
Min length2

Characters and Unicode

Total characters999
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowYes
4th rowYes
5th rowNo
ValueCountFrequency (%)
yes 327
97.3%
no 9
 
2.7%
2023-12-09T21:43:55.086002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 327
32.7%
e 327
32.7%
s 327
32.7%
N 9
 
0.9%
o 9
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 663
66.4%
Uppercase Letter 336
33.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 327
49.3%
s 327
49.3%
o 9
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
Y 327
97.3%
N 9
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 999
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 327
32.7%
e 327
32.7%
s 327
32.7%
N 9
 
0.9%
o 9
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 999
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 327
32.7%
e 327
32.7%
s 327
32.7%
N 9
 
0.9%
o 9
 
0.9%

qbiketype2
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing664
Missing (%)66.4%
Memory size40.2 KiB
2023-12-09T21:43:55.193588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.020833333
Min length2

Characters and Unicode

Total characters679
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 329
97.9%
yes 7
 
2.1%
2023-12-09T21:43:55.417909image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 329
48.5%
o 329
48.5%
Y 7
 
1.0%
e 7
 
1.0%
s 7
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 343
50.5%
Uppercase Letter 336
49.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 329
95.9%
e 7
 
2.0%
s 7
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
N 329
97.9%
Y 7
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 679
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 329
48.5%
o 329
48.5%
Y 7
 
1.0%
e 7
 
1.0%
s 7
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 679
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 329
48.5%
o 329
48.5%
Y 7
 
1.0%
e 7
 
1.0%
s 7
 
1.0%

qbiketype3
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing664
Missing (%)66.4%
Memory size40.2 KiB
2023-12-09T21:43:55.528879image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.017857143
Min length2

Characters and Unicode

Total characters678
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowYes
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 330
98.2%
yes 6
 
1.8%
2023-12-09T21:43:55.750639image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 330
48.7%
o 330
48.7%
Y 6
 
0.9%
e 6
 
0.9%
s 6
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 342
50.4%
Uppercase Letter 336
49.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 330
96.5%
e 6
 
1.8%
s 6
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
N 330
98.2%
Y 6
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 678
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 330
48.7%
o 330
48.7%
Y 6
 
0.9%
e 6
 
0.9%
s 6
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 678
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 330
48.7%
o 330
48.7%
Y 6
 
0.9%
e 6
 
0.9%
s 6
 
0.9%

qbiketype4
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing664
Missing (%)66.4%
Memory size40.2 KiB
2023-12-09T21:43:55.863034image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.00297619
Min length2

Characters and Unicode

Total characters673
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 335
99.7%
yes 1
 
0.3%
2023-12-09T21:43:56.096749image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 335
49.8%
o 335
49.8%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 337
50.1%
Uppercase Letter 336
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 335
99.4%
e 1
 
0.3%
s 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 335
99.7%
Y 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 673
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 335
49.8%
o 335
49.8%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 673
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 335
49.8%
o 335
49.8%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

qbiketype5
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing664
Missing (%)66.4%
Memory size40.2 KiB
2023-12-09T21:43:56.208228image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.00297619
Min length2

Characters and Unicode

Total characters673
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 335
99.7%
yes 1
 
0.3%
2023-12-09T21:43:56.437412image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 335
49.8%
o 335
49.8%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 337
50.1%
Uppercase Letter 336
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 335
99.4%
e 1
 
0.3%
s 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 335
99.7%
Y 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 673
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 335
49.8%
o 335
49.8%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 673
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 335
49.8%
o 335
49.8%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

qbikestore1
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing664
Missing (%)66.4%
Memory size40.3 KiB
2023-12-09T21:43:56.552549image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.05952381
Min length2

Characters and Unicode

Total characters692
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 316
94.0%
yes 20
 
6.0%
2023-12-09T21:43:56.792320image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 316
45.7%
o 316
45.7%
Y 20
 
2.9%
e 20
 
2.9%
s 20
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 356
51.4%
Uppercase Letter 336
48.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 316
88.8%
e 20
 
5.6%
s 20
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
N 316
94.0%
Y 20
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 692
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 316
45.7%
o 316
45.7%
Y 20
 
2.9%
e 20
 
2.9%
s 20
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 692
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 316
45.7%
o 316
45.7%
Y 20
 
2.9%
e 20
 
2.9%
s 20
 
2.9%

qbikestore2
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing664
Missing (%)66.4%
Memory size40.4 KiB
2023-12-09T21:43:56.914204image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.571428571
Min length2

Characters and Unicode

Total characters864
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
yes 192
57.1%
no 144
42.9%
2023-12-09T21:43:57.156798image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 192
22.2%
e 192
22.2%
s 192
22.2%
N 144
16.7%
o 144
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 528
61.1%
Uppercase Letter 336
38.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 192
36.4%
s 192
36.4%
o 144
27.3%
Uppercase Letter
ValueCountFrequency (%)
Y 192
57.1%
N 144
42.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 864
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 192
22.2%
e 192
22.2%
s 192
22.2%
N 144
16.7%
o 144
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 864
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 192
22.2%
e 192
22.2%
s 192
22.2%
N 144
16.7%
o 144
16.7%

qbikestore3
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing664
Missing (%)66.4%
Memory size40.3 KiB
2023-12-09T21:43:57.280997image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.119047619
Min length2

Characters and Unicode

Total characters712
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 296
88.1%
yes 40
 
11.9%
2023-12-09T21:43:57.522788image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 296
41.6%
o 296
41.6%
Y 40
 
5.6%
e 40
 
5.6%
s 40
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 376
52.8%
Uppercase Letter 336
47.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 296
78.7%
e 40
 
10.6%
s 40
 
10.6%
Uppercase Letter
ValueCountFrequency (%)
N 296
88.1%
Y 40
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 712
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 296
41.6%
o 296
41.6%
Y 40
 
5.6%
e 40
 
5.6%
s 40
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 712
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 296
41.6%
o 296
41.6%
Y 40
 
5.6%
e 40
 
5.6%
s 40
 
5.6%

qbikestore4
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing664
Missing (%)66.4%
Memory size40.3 KiB
2023-12-09T21:43:57.643036image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.19047619
Min length2

Characters and Unicode

Total characters736
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 272
81.0%
yes 64
 
19.0%
2023-12-09T21:43:57.876137image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 272
37.0%
o 272
37.0%
Y 64
 
8.7%
e 64
 
8.7%
s 64
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 400
54.3%
Uppercase Letter 336
45.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 272
68.0%
e 64
 
16.0%
s 64
 
16.0%
Uppercase Letter
ValueCountFrequency (%)
N 272
81.0%
Y 64
 
19.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 736
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 272
37.0%
o 272
37.0%
Y 64
 
8.7%
e 64
 
8.7%
s 64
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 736
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 272
37.0%
o 272
37.0%
Y 64
 
8.7%
e 64
 
8.7%
s 64
 
8.7%

qbikestore5
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing664
Missing (%)66.4%
Memory size40.2 KiB
2023-12-09T21:43:57.983024image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.008928571
Min length2

Characters and Unicode

Total characters675
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 333
99.1%
yes 3
 
0.9%
2023-12-09T21:43:58.212238image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 333
49.3%
o 333
49.3%
Y 3
 
0.4%
e 3
 
0.4%
s 3
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 339
50.2%
Uppercase Letter 336
49.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 333
98.2%
e 3
 
0.9%
s 3
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
N 333
99.1%
Y 3
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 675
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 333
49.3%
o 333
49.3%
Y 3
 
0.4%
e 3
 
0.4%
s 3
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 675
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 333
49.3%
o 333
49.3%
Y 3
 
0.4%
e 3
 
0.4%
s 3
 
0.4%

qbikestore6
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing664
Missing (%)66.4%
Memory size40.2 KiB
2023-12-09T21:43:58.320438image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.029761905
Min length2

Characters and Unicode

Total characters682
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 326
97.0%
yes 10
 
3.0%
2023-12-09T21:43:59.125173image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 326
47.8%
o 326
47.8%
Y 10
 
1.5%
e 10
 
1.5%
s 10
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 346
50.7%
Uppercase Letter 336
49.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 326
94.2%
e 10
 
2.9%
s 10
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
N 326
97.0%
Y 10
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 682
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 326
47.8%
o 326
47.8%
Y 10
 
1.5%
e 10
 
1.5%
s 10
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 682
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 326
47.8%
o 326
47.8%
Y 10
 
1.5%
e 10
 
1.5%
s 10
 
1.5%

qbikestore7
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing664
Missing (%)66.4%
Memory size40.2 KiB
2023-12-09T21:43:59.234248image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.044642857
Min length2

Characters and Unicode

Total characters687
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 321
95.5%
yes 15
 
4.5%
2023-12-09T21:43:59.461221image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 321
46.7%
o 321
46.7%
Y 15
 
2.2%
e 15
 
2.2%
s 15
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 351
51.1%
Uppercase Letter 336
48.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 321
91.5%
e 15
 
4.3%
s 15
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
N 321
95.5%
Y 15
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 687
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 321
46.7%
o 321
46.7%
Y 15
 
2.2%
e 15
 
2.2%
s 15
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 687
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 321
46.7%
o 321
46.7%
Y 15
 
2.2%
e 15
 
2.2%
s 15
 
2.2%

qbikestore8
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing664
Missing (%)66.4%
Memory size40.2 KiB
2023-12-09T21:43:59.568546image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.00297619
Min length2

Characters and Unicode

Total characters673
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 335
99.7%
yes 1
 
0.3%
2023-12-09T21:43:59.792479image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 335
49.8%
o 335
49.8%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 337
50.1%
Uppercase Letter 336
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 335
99.4%
e 1
 
0.3%
s 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 335
99.7%
Y 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 673
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 335
49.8%
o 335
49.8%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 673
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 335
49.8%
o 335
49.8%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

qbikestore9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing664
Missing (%)66.4%
Memory size40.2 KiB
2023-12-09T21:43:59.893732image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters672
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 336
100.0%
2023-12-09T21:44:00.110605image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 336
50.0%
o 336
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 336
50.0%
Lowercase Letter 336
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 336
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 336
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 672
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 336
50.0%
o 336
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 672
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 336
50.0%
o 336
50.0%

qbikeride
Text

MISSING 

Distinct7
Distinct (%)0.8%
Missing103
Missing (%)10.3%
Memory size63.3 KiB
2023-12-09T21:44:00.292496image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length32
Median length5
Mean length11.47491639
Min length5

Characters and Unicode

Total characters10293
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowA few times a year
2nd rowNever
3rd rowNever
4th rowNever
5th rowA few times a year
ValueCountFrequency (%)
never 533
23.0%
a 490
21.2%
times 206
 
8.9%
month 133
 
5.7%
few 127
 
5.5%
year 127
 
5.5%
once 112
 
4.8%
several 79
 
3.4%
more 58
 
2.5%
or 58
 
2.5%
Other values (9) 392
16.9%
2023-12-09T21:44:00.595830image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2161
21.0%
1418
13.8%
r 900
 
8.7%
a 713
 
6.9%
v 612
 
5.9%
N 533
 
5.2%
t 492
 
4.8%
m 397
 
3.9%
o 348
 
3.4%
i 341
 
3.3%
Other values (17) 2378
23.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7978
77.5%
Space Separator 1418
 
13.8%
Uppercase Letter 897
 
8.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2161
27.1%
r 900
11.3%
a 713
 
8.9%
v 612
 
7.7%
t 492
 
6.2%
m 397
 
5.0%
o 348
 
4.4%
i 341
 
4.3%
s 306
 
3.8%
n 290
 
3.6%
Other values (10) 1418
17.8%
Uppercase Letter
ValueCountFrequency (%)
N 533
59.4%
A 181
 
20.2%
S 79
 
8.8%
O 58
 
6.5%
P 45
 
5.0%
R 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1418
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8875
86.2%
Common 1418
 
13.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2161
24.3%
r 900
10.1%
a 713
 
8.0%
v 612
 
6.9%
N 533
 
6.0%
t 492
 
5.5%
m 397
 
4.5%
o 348
 
3.9%
i 341
 
3.8%
s 306
 
3.4%
Other values (16) 2072
23.3%
Common
ValueCountFrequency (%)
1418
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10293
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2161
21.0%
1418
13.8%
r 900
 
8.7%
a 713
 
6.9%
v 612
 
5.9%
N 533
 
5.2%
t 492
 
4.8%
m 397
 
3.9%
o 348
 
3.4%
i 341
 
3.3%
Other values (17) 2378
23.1%

qbiketo
Text

MISSING 

Distinct2
Distinct (%)0.6%
Missing684
Missing (%)68.4%
Memory size39.8 KiB
2023-12-09T21:44:00.725092image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.316455696
Min length2

Characters and Unicode

Total characters732
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 216
68.4%
yes 100
31.6%
2023-12-09T21:44:00.957998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 216
29.5%
o 216
29.5%
Y 100
13.7%
e 100
13.7%
s 100
13.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 416
56.8%
Uppercase Letter 316
43.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 216
51.9%
e 100
24.0%
s 100
24.0%
Uppercase Letter
ValueCountFrequency (%)
N 216
68.4%
Y 100
31.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 732
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 216
29.5%
o 216
29.5%
Y 100
13.7%
e 100
13.7%
s 100
13.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 732
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 216
29.5%
o 216
29.5%
Y 100
13.7%
e 100
13.7%
s 100
13.7%

qbikedays
Text

MISSING 

Distinct10
Distinct (%)10.1%
Missing901
Missing (%)90.1%
Memory size33.9 KiB
2023-12-09T21:44:01.092495image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.050505051
Min length1

Characters and Unicode

Total characters104
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row1
2nd row1
3rd row1
4th row3
5th row10
ValueCountFrequency (%)
2 31
31.3%
1 27
27.3%
3 16
16.2%
4 7
 
7.1%
5 5
 
5.1%
7 4
 
4.0%
10 4
 
4.0%
6 3
 
3.0%
40 1
 
1.0%
0 1
 
1.0%
2023-12-09T21:44:01.351810image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 31
29.8%
1 31
29.8%
3 16
15.4%
4 8
 
7.7%
0 6
 
5.8%
5 5
 
4.8%
7 4
 
3.8%
6 3
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 104
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 31
29.8%
1 31
29.8%
3 16
15.4%
4 8
 
7.7%
0 6
 
5.8%
5 5
 
4.8%
7 4
 
3.8%
6 3
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Common 104
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 31
29.8%
1 31
29.8%
3 16
15.4%
4 8
 
7.7%
0 6
 
5.8%
5 5
 
4.8%
7 4
 
3.8%
6 3
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 31
29.8%
1 31
29.8%
3 16
15.4%
4 8
 
7.7%
0 6
 
5.8%
5 5
 
4.8%
7 4
 
3.8%
6 3
 
2.9%

qbikewhy1
Text

MISSING 

Distinct2
Distinct (%)1.0%
Missing809
Missing (%)80.9%
Memory size36.5 KiB
2023-12-09T21:44:01.487846image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.308900524
Min length2

Characters and Unicode

Total characters441
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 132
69.1%
yes 59
30.9%
2023-12-09T21:44:01.742891image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 132
29.9%
o 132
29.9%
Y 59
13.4%
e 59
13.4%
s 59
13.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 250
56.7%
Uppercase Letter 191
43.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 132
52.8%
e 59
23.6%
s 59
23.6%
Uppercase Letter
ValueCountFrequency (%)
N 132
69.1%
Y 59
30.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 441
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 132
29.9%
o 132
29.9%
Y 59
13.4%
e 59
13.4%
s 59
13.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 132
29.9%
o 132
29.9%
Y 59
13.4%
e 59
13.4%
s 59
13.4%

qbikewhy2
Text

MISSING 

Distinct2
Distinct (%)1.0%
Missing809
Missing (%)80.9%
Memory size36.4 KiB
2023-12-09T21:44:01.858814image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.068062827
Min length2

Characters and Unicode

Total characters395
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 178
93.2%
yes 13
 
6.8%
2023-12-09T21:44:02.095109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 178
45.1%
o 178
45.1%
Y 13
 
3.3%
e 13
 
3.3%
s 13
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 204
51.6%
Uppercase Letter 191
48.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 178
87.3%
e 13
 
6.4%
s 13
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
N 178
93.2%
Y 13
 
6.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 395
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 178
45.1%
o 178
45.1%
Y 13
 
3.3%
e 13
 
3.3%
s 13
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 395
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 178
45.1%
o 178
45.1%
Y 13
 
3.3%
e 13
 
3.3%
s 13
 
3.3%

qbikewhy3
Text

MISSING 

Distinct2
Distinct (%)1.0%
Missing809
Missing (%)80.9%
Memory size36.5 KiB
2023-12-09T21:44:02.214666image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.67539267
Min length2

Characters and Unicode

Total characters511
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 129
67.5%
no 62
32.5%
2023-12-09T21:44:02.455191image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 129
25.2%
e 129
25.2%
s 129
25.2%
N 62
12.1%
o 62
12.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 320
62.6%
Uppercase Letter 191
37.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 129
40.3%
s 129
40.3%
o 62
19.4%
Uppercase Letter
ValueCountFrequency (%)
Y 129
67.5%
N 62
32.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 511
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 129
25.2%
e 129
25.2%
s 129
25.2%
N 62
12.1%
o 62
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 129
25.2%
e 129
25.2%
s 129
25.2%
N 62
12.1%
o 62
12.1%

qbikewhy4
Text

MISSING 

Distinct2
Distinct (%)1.0%
Missing809
Missing (%)80.9%
Memory size36.4 KiB
2023-12-09T21:44:02.574615image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.141361257
Min length2

Characters and Unicode

Total characters409
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 164
85.9%
yes 27
 
14.1%
2023-12-09T21:44:02.812586image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 164
40.1%
o 164
40.1%
Y 27
 
6.6%
e 27
 
6.6%
s 27
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 218
53.3%
Uppercase Letter 191
46.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 164
75.2%
e 27
 
12.4%
s 27
 
12.4%
Uppercase Letter
ValueCountFrequency (%)
N 164
85.9%
Y 27
 
14.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 409
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 164
40.1%
o 164
40.1%
Y 27
 
6.6%
e 27
 
6.6%
s 27
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 409
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 164
40.1%
o 164
40.1%
Y 27
 
6.6%
e 27
 
6.6%
s 27
 
6.6%

qbikewhy5
Text

MISSING 

Distinct2
Distinct (%)1.0%
Missing809
Missing (%)80.9%
Memory size36.4 KiB
2023-12-09T21:44:02.930598image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.09947644
Min length2

Characters and Unicode

Total characters401
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowYes
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 172
90.1%
yes 19
 
9.9%
2023-12-09T21:44:03.172502image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 172
42.9%
o 172
42.9%
Y 19
 
4.7%
e 19
 
4.7%
s 19
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 210
52.4%
Uppercase Letter 191
47.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 172
81.9%
e 19
 
9.0%
s 19
 
9.0%
Uppercase Letter
ValueCountFrequency (%)
N 172
90.1%
Y 19
 
9.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 401
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 172
42.9%
o 172
42.9%
Y 19
 
4.7%
e 19
 
4.7%
s 19
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 401
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 172
42.9%
o 172
42.9%
Y 19
 
4.7%
e 19
 
4.7%
s 19
 
4.7%

qbikewhy6
Text

MISSING 

Distinct2
Distinct (%)1.0%
Missing809
Missing (%)80.9%
Memory size36.4 KiB
2023-12-09T21:44:03.281000image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.010471204
Min length2

Characters and Unicode

Total characters384
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 189
99.0%
yes 2
 
1.0%
2023-12-09T21:44:03.517803image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 189
49.2%
o 189
49.2%
Y 2
 
0.5%
e 2
 
0.5%
s 2
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 193
50.3%
Uppercase Letter 191
49.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 189
97.9%
e 2
 
1.0%
s 2
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
N 189
99.0%
Y 2
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 384
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 189
49.2%
o 189
49.2%
Y 2
 
0.5%
e 2
 
0.5%
s 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 189
49.2%
o 189
49.2%
Y 2
 
0.5%
e 2
 
0.5%
s 2
 
0.5%

qbikewhy7
Text

MISSING 

Distinct2
Distinct (%)1.0%
Missing809
Missing (%)80.9%
Memory size36.4 KiB
2023-12-09T21:44:03.633184image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.010471204
Min length2

Characters and Unicode

Total characters384
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 189
99.0%
yes 2
 
1.0%
2023-12-09T21:44:03.857066image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 189
49.2%
o 189
49.2%
Y 2
 
0.5%
e 2
 
0.5%
s 2
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 193
50.3%
Uppercase Letter 191
49.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 189
97.9%
e 2
 
1.0%
s 2
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
N 189
99.0%
Y 2
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 384
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 189
49.2%
o 189
49.2%
Y 2
 
0.5%
e 2
 
0.5%
s 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 189
49.2%
o 189
49.2%
Y 2
 
0.5%
e 2
 
0.5%
s 2
 
0.5%

qbikewhy8
Text

MISSING 

Distinct2
Distinct (%)1.0%
Missing809
Missing (%)80.9%
Memory size36.4 KiB
2023-12-09T21:44:03.964098image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.015706806
Min length2

Characters and Unicode

Total characters385
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 188
98.4%
yes 3
 
1.6%
2023-12-09T21:44:04.192418image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 188
48.8%
o 188
48.8%
Y 3
 
0.8%
e 3
 
0.8%
s 3
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 194
50.4%
Uppercase Letter 191
49.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 188
96.9%
e 3
 
1.5%
s 3
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
N 188
98.4%
Y 3
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 385
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 188
48.8%
o 188
48.8%
Y 3
 
0.8%
e 3
 
0.8%
s 3
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 385
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 188
48.8%
o 188
48.8%
Y 3
 
0.8%
e 3
 
0.8%
s 3
 
0.8%

qbikewhynot1
Text

MISSING 

Distinct2
Distinct (%)0.3%
Missing337
Missing (%)33.7%
Memory size49.0 KiB
2023-12-09T21:44:04.311831image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.254901961
Min length2

Characters and Unicode

Total characters1495
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 494
74.5%
yes 169
 
25.5%
2023-12-09T21:44:04.549080image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 494
33.0%
o 494
33.0%
Y 169
 
11.3%
e 169
 
11.3%
s 169
 
11.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 832
55.7%
Uppercase Letter 663
44.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 494
59.4%
e 169
 
20.3%
s 169
 
20.3%
Uppercase Letter
ValueCountFrequency (%)
N 494
74.5%
Y 169
 
25.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1495
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 494
33.0%
o 494
33.0%
Y 169
 
11.3%
e 169
 
11.3%
s 169
 
11.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 494
33.0%
o 494
33.0%
Y 169
 
11.3%
e 169
 
11.3%
s 169
 
11.3%

qbikewhynot2
Text

MISSING 

Distinct2
Distinct (%)0.3%
Missing337
Missing (%)33.7%
Memory size49.0 KiB
2023-12-09T21:44:04.666423image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.187028658
Min length2

Characters and Unicode

Total characters1450
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 539
81.3%
yes 124
 
18.7%
2023-12-09T21:44:04.895421image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 539
37.2%
o 539
37.2%
Y 124
 
8.6%
e 124
 
8.6%
s 124
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 787
54.3%
Uppercase Letter 663
45.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 539
68.5%
e 124
 
15.8%
s 124
 
15.8%
Uppercase Letter
ValueCountFrequency (%)
N 539
81.3%
Y 124
 
18.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 1450
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 539
37.2%
o 539
37.2%
Y 124
 
8.6%
e 124
 
8.6%
s 124
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 539
37.2%
o 539
37.2%
Y 124
 
8.6%
e 124
 
8.6%
s 124
 
8.6%

qbikewhynot3
Text

MISSING 

Distinct2
Distinct (%)0.3%
Missing337
Missing (%)33.7%
Memory size48.9 KiB
2023-12-09T21:44:05.010402image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.134238311
Min length2

Characters and Unicode

Total characters1415
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 574
86.6%
yes 89
 
13.4%
2023-12-09T21:44:05.243320image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 574
40.6%
o 574
40.6%
Y 89
 
6.3%
e 89
 
6.3%
s 89
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 752
53.1%
Uppercase Letter 663
46.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 574
76.3%
e 89
 
11.8%
s 89
 
11.8%
Uppercase Letter
ValueCountFrequency (%)
N 574
86.6%
Y 89
 
13.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 1415
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 574
40.6%
o 574
40.6%
Y 89
 
6.3%
e 89
 
6.3%
s 89
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1415
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 574
40.6%
o 574
40.6%
Y 89
 
6.3%
e 89
 
6.3%
s 89
 
6.3%

qbikewhynot4
Text

MISSING 

Distinct2
Distinct (%)0.3%
Missing337
Missing (%)33.7%
Memory size49.2 KiB
2023-12-09T21:44:05.383332image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.476621418
Min length2

Characters and Unicode

Total characters1642
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 347
52.3%
yes 316
47.7%
2023-12-09T21:44:05.643627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 347
21.1%
o 347
21.1%
Y 316
19.2%
e 316
19.2%
s 316
19.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 979
59.6%
Uppercase Letter 663
40.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 347
35.4%
e 316
32.3%
s 316
32.3%
Uppercase Letter
ValueCountFrequency (%)
N 347
52.3%
Y 316
47.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 1642
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 347
21.1%
o 347
21.1%
Y 316
19.2%
e 316
19.2%
s 316
19.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1642
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 347
21.1%
o 347
21.1%
Y 316
19.2%
e 316
19.2%
s 316
19.2%

qbikewhynot5
Text

MISSING 

Distinct2
Distinct (%)0.3%
Missing337
Missing (%)33.7%
Memory size48.9 KiB
2023-12-09T21:44:05.756868image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.09653092
Min length2

Characters and Unicode

Total characters1390
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 599
90.3%
yes 64
 
9.7%
2023-12-09T21:44:05.983389image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 599
43.1%
o 599
43.1%
Y 64
 
4.6%
e 64
 
4.6%
s 64
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 727
52.3%
Uppercase Letter 663
47.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 599
82.4%
e 64
 
8.8%
s 64
 
8.8%
Uppercase Letter
ValueCountFrequency (%)
N 599
90.3%
Y 64
 
9.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 1390
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 599
43.1%
o 599
43.1%
Y 64
 
4.6%
e 64
 
4.6%
s 64
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1390
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 599
43.1%
o 599
43.1%
Y 64
 
4.6%
e 64
 
4.6%
s 64
 
4.6%

qbikewhynot6
Text

MISSING 

Distinct2
Distinct (%)0.3%
Missing337
Missing (%)33.7%
Memory size49.0 KiB
2023-12-09T21:44:06.098107image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.152337858
Min length2

Characters and Unicode

Total characters1427
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
no 562
84.8%
yes 101
 
15.2%
2023-12-09T21:44:06.330896image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 562
39.4%
o 562
39.4%
Y 101
 
7.1%
e 101
 
7.1%
s 101
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 764
53.5%
Uppercase Letter 663
46.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 562
73.6%
e 101
 
13.2%
s 101
 
13.2%
Uppercase Letter
ValueCountFrequency (%)
N 562
84.8%
Y 101
 
15.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 1427
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 562
39.4%
o 562
39.4%
Y 101
 
7.1%
e 101
 
7.1%
s 101
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1427
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 562
39.4%
o 562
39.4%
Y 101
 
7.1%
e 101
 
7.1%
s 101
 
7.1%

qbikewhynot7
Text

MISSING 

Distinct2
Distinct (%)0.3%
Missing337
Missing (%)33.7%
Memory size48.9 KiB
2023-12-09T21:44:06.439766image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.043740573
Min length2

Characters and Unicode

Total characters1355
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 634
95.6%
yes 29
 
4.4%
2023-12-09T21:44:06.670846image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 634
46.8%
o 634
46.8%
Y 29
 
2.1%
e 29
 
2.1%
s 29
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 692
51.1%
Uppercase Letter 663
48.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 634
91.6%
e 29
 
4.2%
s 29
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
N 634
95.6%
Y 29
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 1355
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 634
46.8%
o 634
46.8%
Y 29
 
2.1%
e 29
 
2.1%
s 29
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1355
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 634
46.8%
o 634
46.8%
Y 29
 
2.1%
e 29
 
2.1%
s 29
 
2.1%

qbikewhynot8
Text

MISSING 

Distinct2
Distinct (%)0.3%
Missing337
Missing (%)33.7%
Memory size48.9 KiB
2023-12-09T21:44:06.781168image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.001508296
Min length2

Characters and Unicode

Total characters1327
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 662
99.8%
yes 1
 
0.2%
2023-12-09T21:44:07.015254image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 662
49.9%
o 662
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 664
50.0%
Uppercase Letter 663
50.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 662
99.7%
e 1
 
0.2%
s 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 662
99.8%
Y 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 1327
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 662
49.9%
o 662
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 662
49.9%
o 662
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

qbikestolen
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing16
Missing (%)1.6%
Memory size57.5 KiB
2023-12-09T21:44:07.151824image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.181910569
Min length2

Characters and Unicode

Total characters2147
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 805
81.8%
yes 179
 
18.2%
2023-12-09T21:44:07.382571image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 805
37.5%
o 805
37.5%
Y 179
 
8.3%
e 179
 
8.3%
s 179
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1163
54.2%
Uppercase Letter 984
45.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 805
69.2%
e 179
 
15.4%
s 179
 
15.4%
Uppercase Letter
ValueCountFrequency (%)
N 805
81.8%
Y 179
 
18.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 2147
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 805
37.5%
o 805
37.5%
Y 179
 
8.3%
e 179
 
8.3%
s 179
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2147
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 805
37.5%
o 805
37.5%
Y 179
 
8.3%
e 179
 
8.3%
s 179
 
8.3%

qcitibike
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing40
Missing (%)4.0%
Memory size56.8 KiB
2023-12-09T21:44:07.494383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.06875
Min length2

Characters and Unicode

Total characters1986
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 894
93.1%
yes 66
 
6.9%
2023-12-09T21:44:07.722109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 894
45.0%
o 894
45.0%
Y 66
 
3.3%
e 66
 
3.3%
s 66
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1026
51.7%
Uppercase Letter 960
48.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 894
87.1%
e 66
 
6.4%
s 66
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
N 894
93.1%
Y 66
 
6.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 1986
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 894
45.0%
o 894
45.0%
Y 66
 
3.3%
e 66
 
3.3%
s 66
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1986
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 894
45.0%
o 894
45.0%
Y 66
 
3.3%
e 66
 
3.3%
s 66
 
3.3%

qcitibikefreq
Text

MISSING 

Distinct7
Distinct (%)10.8%
Missing935
Missing (%)93.5%
Memory size34.1 KiB
2023-12-09T21:44:07.880429image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length28
Median length19
Mean length17.93846154
Min length5

Characters and Unicode

Total characters1166
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA few times a year
2nd rowLess than a few times a year
3rd rowA few times a year
4th rowA few times a year
5th rowA few times a year
ValueCountFrequency (%)
a 97
33.2%
times 47
16.1%
few 36
 
12.3%
year 28
 
9.6%
week 19
 
6.5%
once 14
 
4.8%
month 14
 
4.8%
several 11
 
3.8%
less 11
 
3.8%
than 11
 
3.8%
2023-12-09T21:44:08.178558image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
227
19.5%
e 196
16.8%
a 126
10.8%
t 72
 
6.2%
s 69
 
5.9%
m 61
 
5.2%
w 55
 
4.7%
i 51
 
4.4%
r 39
 
3.3%
n 39
 
3.3%
Other values (13) 231
19.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 874
75.0%
Space Separator 227
 
19.5%
Uppercase Letter 65
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 196
22.4%
a 126
14.4%
t 72
 
8.2%
s 69
 
7.9%
m 61
 
7.0%
w 55
 
6.3%
i 51
 
5.8%
r 39
 
4.5%
n 39
 
4.5%
f 36
 
4.1%
Other values (7) 130
14.9%
Uppercase Letter
ValueCountFrequency (%)
A 25
38.5%
O 14
21.5%
L 11
16.9%
S 11
16.9%
D 4
 
6.2%
Space Separator
ValueCountFrequency (%)
227
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 939
80.5%
Common 227
 
19.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 196
20.9%
a 126
13.4%
t 72
 
7.7%
s 69
 
7.3%
m 61
 
6.5%
w 55
 
5.9%
i 51
 
5.4%
r 39
 
4.2%
n 39
 
4.2%
f 36
 
3.8%
Other values (12) 195
20.8%
Common
ValueCountFrequency (%)
227
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1166
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
227
19.5%
e 196
16.8%
a 126
10.8%
t 72
 
6.2%
s 69
 
5.9%
m 61
 
5.2%
w 55
 
4.7%
i 51
 
4.4%
r 39
 
3.3%
n 39
 
3.3%
Other values (13) 231
19.8%

gcitibk1_qcitibikeissues1
Text

MISSING 

Distinct5
Distinct (%)7.6%
Missing934
Missing (%)93.4%
Memory size34.1 KiB
2023-12-09T21:44:08.354123image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length21
Median length19
Mean length17.51515152
Min length5

Characters and Unicode

Total characters1156
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNever
2nd rowSomewhat frequently
3rd rowNot very frequently
4th rowSomewhat frequently
5th rowNever
ValueCountFrequency (%)
frequently 61
37.4%
very 31
19.0%
not 28
17.2%
somewhat 22
 
13.5%
at 8
 
4.9%
all 8
 
4.9%
never 5
 
3.1%
2023-12-09T21:44:08.652815image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 185
16.0%
t 119
10.3%
97
 
8.4%
r 97
 
8.4%
y 92
 
8.0%
l 77
 
6.7%
f 61
 
5.3%
q 61
 
5.3%
u 61
 
5.3%
n 61
 
5.3%
Other values (9) 245
21.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 993
85.9%
Space Separator 97
 
8.4%
Uppercase Letter 66
 
5.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 185
18.6%
t 119
12.0%
r 97
9.8%
y 92
9.3%
l 77
7.8%
f 61
 
6.1%
q 61
 
6.1%
u 61
 
6.1%
n 61
 
6.1%
o 50
 
5.0%
Other values (5) 129
13.0%
Uppercase Letter
ValueCountFrequency (%)
N 33
50.0%
S 22
33.3%
V 11
 
16.7%
Space Separator
ValueCountFrequency (%)
97
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1059
91.6%
Common 97
 
8.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 185
17.5%
t 119
11.2%
r 97
9.2%
y 92
8.7%
l 77
 
7.3%
f 61
 
5.8%
q 61
 
5.8%
u 61
 
5.8%
n 61
 
5.8%
o 50
 
4.7%
Other values (8) 195
18.4%
Common
ValueCountFrequency (%)
97
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 185
16.0%
t 119
10.3%
97
 
8.4%
r 97
 
8.4%
y 92
 
8.0%
l 77
 
6.7%
f 61
 
5.3%
q 61
 
5.3%
u 61
 
5.3%
n 61
 
5.3%
Other values (9) 245
21.2%

gcitibk1_qcitibikeissues2
Text

MISSING 

Distinct5
Distinct (%)7.6%
Missing934
Missing (%)93.4%
Memory size34.1 KiB
2023-12-09T21:44:08.824113image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length21
Median length19
Mean length17.93939394
Min length5

Characters and Unicode

Total characters1184
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNever
2nd rowNot very frequently
3rd rowNot very frequently
4th rowNot at all frequently
5th rowNot very frequently
ValueCountFrequency (%)
frequently 62
36.7%
not 32
18.9%
very 31
18.3%
somewhat 22
 
13.0%
at 9
 
5.3%
all 9
 
5.3%
never 4
 
2.4%
2023-12-09T21:44:09.119403image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 185
15.6%
t 125
10.6%
103
8.7%
r 97
 
8.2%
y 93
 
7.9%
l 80
 
6.8%
q 62
 
5.2%
f 62
 
5.2%
u 62
 
5.2%
n 62
 
5.2%
Other values (9) 253
21.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1015
85.7%
Space Separator 103
 
8.7%
Uppercase Letter 66
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 185
18.2%
t 125
12.3%
r 97
9.6%
y 93
9.2%
l 80
7.9%
q 62
 
6.1%
f 62
 
6.1%
u 62
 
6.1%
n 62
 
6.1%
o 54
 
5.3%
Other values (5) 133
13.1%
Uppercase Letter
ValueCountFrequency (%)
N 36
54.5%
S 22
33.3%
V 8
 
12.1%
Space Separator
ValueCountFrequency (%)
103
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1081
91.3%
Common 103
 
8.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 185
17.1%
t 125
11.6%
r 97
9.0%
y 93
8.6%
l 80
7.4%
q 62
 
5.7%
f 62
 
5.7%
u 62
 
5.7%
n 62
 
5.7%
o 54
 
5.0%
Other values (8) 199
18.4%
Common
ValueCountFrequency (%)
103
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 185
15.6%
t 125
10.6%
103
8.7%
r 97
 
8.2%
y 93
 
7.9%
l 80
 
6.8%
q 62
 
5.2%
f 62
 
5.2%
u 62
 
5.2%
n 62
 
5.2%
Other values (9) 253
21.4%

qnocitibike01
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing106
Missing (%)10.6%
Memory size55.1 KiB
2023-12-09T21:44:09.236618image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.138702461
Min length2

Characters and Unicode

Total characters1912
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 770
86.1%
yes 124
 
13.9%
2023-12-09T21:44:09.464657image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 770
40.3%
o 770
40.3%
Y 124
 
6.5%
e 124
 
6.5%
s 124
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1018
53.2%
Uppercase Letter 894
46.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 770
75.6%
e 124
 
12.2%
s 124
 
12.2%
Uppercase Letter
ValueCountFrequency (%)
N 770
86.1%
Y 124
 
13.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 1912
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 770
40.3%
o 770
40.3%
Y 124
 
6.5%
e 124
 
6.5%
s 124
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1912
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 770
40.3%
o 770
40.3%
Y 124
 
6.5%
e 124
 
6.5%
s 124
 
6.5%

qnocitibike02
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing106
Missing (%)10.6%
Memory size55.2 KiB
2023-12-09T21:44:09.586612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.24049217
Min length2

Characters and Unicode

Total characters2003
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 679
76.0%
yes 215
 
24.0%
2023-12-09T21:44:09.827393image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 679
33.9%
o 679
33.9%
Y 215
 
10.7%
e 215
 
10.7%
s 215
 
10.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1109
55.4%
Uppercase Letter 894
44.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 679
61.2%
e 215
 
19.4%
s 215
 
19.4%
Uppercase Letter
ValueCountFrequency (%)
N 679
76.0%
Y 215
 
24.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2003
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 679
33.9%
o 679
33.9%
Y 215
 
10.7%
e 215
 
10.7%
s 215
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2003
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 679
33.9%
o 679
33.9%
Y 215
 
10.7%
e 215
 
10.7%
s 215
 
10.7%

qnocitibike03
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing106
Missing (%)10.6%
Memory size55.0 KiB
2023-12-09T21:44:09.938494image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.080536913
Min length2

Characters and Unicode

Total characters1860
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 822
91.9%
yes 72
 
8.1%
2023-12-09T21:44:10.161526image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 822
44.2%
o 822
44.2%
Y 72
 
3.9%
e 72
 
3.9%
s 72
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 966
51.9%
Uppercase Letter 894
48.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 822
85.1%
e 72
 
7.5%
s 72
 
7.5%
Uppercase Letter
ValueCountFrequency (%)
N 822
91.9%
Y 72
 
8.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 1860
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 822
44.2%
o 822
44.2%
Y 72
 
3.9%
e 72
 
3.9%
s 72
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1860
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 822
44.2%
o 822
44.2%
Y 72
 
3.9%
e 72
 
3.9%
s 72
 
3.9%

qnocitibike04
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing106
Missing (%)10.6%
Memory size55.1 KiB
2023-12-09T21:44:10.279814image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.135346756
Min length2

Characters and Unicode

Total characters1909
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowYes
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 773
86.5%
yes 121
 
13.5%
2023-12-09T21:44:10.517792image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 773
40.5%
o 773
40.5%
Y 121
 
6.3%
e 121
 
6.3%
s 121
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1015
53.2%
Uppercase Letter 894
46.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 773
76.2%
e 121
 
11.9%
s 121
 
11.9%
Uppercase Letter
ValueCountFrequency (%)
N 773
86.5%
Y 121
 
13.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1909
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 773
40.5%
o 773
40.5%
Y 121
 
6.3%
e 121
 
6.3%
s 121
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1909
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 773
40.5%
o 773
40.5%
Y 121
 
6.3%
e 121
 
6.3%
s 121
 
6.3%

qnocitibike05
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing106
Missing (%)10.6%
Memory size55.0 KiB
2023-12-09T21:44:10.628776image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.01901566
Min length2

Characters and Unicode

Total characters1805
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 877
98.1%
yes 17
 
1.9%
2023-12-09T21:44:10.850753image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 877
48.6%
o 877
48.6%
Y 17
 
0.9%
e 17
 
0.9%
s 17
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 911
50.5%
Uppercase Letter 894
49.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 877
96.3%
e 17
 
1.9%
s 17
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
N 877
98.1%
Y 17
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 1805
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 877
48.6%
o 877
48.6%
Y 17
 
0.9%
e 17
 
0.9%
s 17
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1805
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 877
48.6%
o 877
48.6%
Y 17
 
0.9%
e 17
 
0.9%
s 17
 
0.9%

qnocitibike06
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing106
Missing (%)10.6%
Memory size55.1 KiB
2023-12-09T21:44:10.966134image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.180089485
Min length2

Characters and Unicode

Total characters1949
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 733
82.0%
yes 161
 
18.0%
2023-12-09T21:44:11.204171image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 733
37.6%
o 733
37.6%
Y 161
 
8.3%
e 161
 
8.3%
s 161
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1055
54.1%
Uppercase Letter 894
45.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 733
69.5%
e 161
 
15.3%
s 161
 
15.3%
Uppercase Letter
ValueCountFrequency (%)
N 733
82.0%
Y 161
 
18.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1949
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 733
37.6%
o 733
37.6%
Y 161
 
8.3%
e 161
 
8.3%
s 161
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1949
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 733
37.6%
o 733
37.6%
Y 161
 
8.3%
e 161
 
8.3%
s 161
 
8.3%

qnocitibike07
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing106
Missing (%)10.6%
Memory size55.3 KiB
2023-12-09T21:44:11.331105image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.35458613
Min length2

Characters and Unicode

Total characters2105
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 577
64.5%
yes 317
35.5%
2023-12-09T21:44:11.584015image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 577
27.4%
o 577
27.4%
Y 317
15.1%
e 317
15.1%
s 317
15.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1211
57.5%
Uppercase Letter 894
42.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 577
47.6%
e 317
26.2%
s 317
26.2%
Uppercase Letter
ValueCountFrequency (%)
N 577
64.5%
Y 317
35.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 2105
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 577
27.4%
o 577
27.4%
Y 317
15.1%
e 317
15.1%
s 317
15.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2105
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 577
27.4%
o 577
27.4%
Y 317
15.1%
e 317
15.1%
s 317
15.1%

qnocitibike08
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing106
Missing (%)10.6%
Memory size55.0 KiB
2023-12-09T21:44:11.695045image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.029082774
Min length2

Characters and Unicode

Total characters1814
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 868
97.1%
yes 26
 
2.9%
2023-12-09T21:44:11.913699image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 868
47.9%
o 868
47.9%
Y 26
 
1.4%
e 26
 
1.4%
s 26
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 920
50.7%
Uppercase Letter 894
49.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 868
94.3%
e 26
 
2.8%
s 26
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
N 868
97.1%
Y 26
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 1814
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 868
47.9%
o 868
47.9%
Y 26
 
1.4%
e 26
 
1.4%
s 26
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1814
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 868
47.9%
o 868
47.9%
Y 26
 
1.4%
e 26
 
1.4%
s 26
 
1.4%

qnocitibike09
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing106
Missing (%)10.6%
Memory size55.0 KiB
2023-12-09T21:44:12.780759image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.065995526
Min length2

Characters and Unicode

Total characters1847
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 835
93.4%
yes 59
 
6.6%
2023-12-09T21:44:13.010844image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 835
45.2%
o 835
45.2%
Y 59
 
3.2%
e 59
 
3.2%
s 59
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 953
51.6%
Uppercase Letter 894
48.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 835
87.6%
e 59
 
6.2%
s 59
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
N 835
93.4%
Y 59
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 1847
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 835
45.2%
o 835
45.2%
Y 59
 
3.2%
e 59
 
3.2%
s 59
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1847
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 835
45.2%
o 835
45.2%
Y 59
 
3.2%
e 59
 
3.2%
s 59
 
3.2%

qnocitibike10
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing106
Missing (%)10.6%
Memory size55.0 KiB
2023-12-09T21:44:13.120953image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.030201342
Min length2

Characters and Unicode

Total characters1815
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 867
97.0%
yes 27
 
3.0%
2023-12-09T21:44:13.351482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 867
47.8%
o 867
47.8%
Y 27
 
1.5%
e 27
 
1.5%
s 27
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 921
50.7%
Uppercase Letter 894
49.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 867
94.1%
e 27
 
2.9%
s 27
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
N 867
97.0%
Y 27
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1815
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 867
47.8%
o 867
47.8%
Y 27
 
1.5%
e 27
 
1.5%
s 27
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1815
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 867
47.8%
o 867
47.8%
Y 27
 
1.5%
e 27
 
1.5%
s 27
 
1.5%

qnocitibike11
Text

MISSING 

Distinct2
Distinct (%)0.2%
Missing106
Missing (%)10.6%
Memory size55.0 KiB
2023-12-09T21:44:13.466707image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.005592841
Min length2

Characters and Unicode

Total characters1793
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 889
99.4%
yes 5
 
0.6%
2023-12-09T21:44:13.682677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 889
49.6%
o 889
49.6%
Y 5
 
0.3%
e 5
 
0.3%
s 5
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 899
50.1%
Uppercase Letter 894
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 889
98.9%
e 5
 
0.6%
s 5
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
N 889
99.4%
Y 5
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 1793
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 889
49.6%
o 889
49.6%
Y 5
 
0.3%
e 5
 
0.3%
s 5
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1793
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 889
49.6%
o 889
49.6%
Y 5
 
0.3%
e 5
 
0.3%
s 5
 
0.3%

gfreight1b_qfreight1_ma
Text

MISSING 

Distinct8
Distinct (%)0.9%
Missing119
Missing (%)11.9%
Memory size70.2 KiB
2023-12-09T21:44:13.840207image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length28
Median length20
Mean length20.08286039
Min length5

Characters and Unicode

Total characters17693
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLess than a few times a year
2nd rowLess than a few times a year
3rd rowA few times a year
4th rowLess than a few times a year
5th rowA few times a month
ValueCountFrequency (%)
a 1359
30.8%
times 617
14.0%
few 548
12.4%
year 451
 
10.2%
less 374
 
8.5%
than 374
 
8.5%
week 205
 
4.6%
once 194
 
4.4%
month 155
 
3.5%
several 69
 
1.6%
Other values (2) 70
 
1.6%
2023-12-09T21:44:14.139635image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3535
20.0%
e 2802
15.8%
a 2114
11.9%
s 1400
 
7.9%
t 1146
 
6.5%
m 772
 
4.4%
w 753
 
4.3%
n 723
 
4.1%
i 652
 
3.7%
f 583
 
3.3%
Other values (16) 3213
18.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13277
75.0%
Space Separator 3535
 
20.0%
Uppercase Letter 881
 
5.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2802
21.1%
a 2114
15.9%
s 1400
10.5%
t 1146
8.6%
m 772
 
5.8%
w 753
 
5.7%
n 723
 
5.4%
i 652
 
4.9%
f 583
 
4.4%
h 529
 
4.0%
Other values (9) 1803
13.6%
Uppercase Letter
ValueCountFrequency (%)
L 374
42.5%
O 194
22.0%
A 174
19.8%
S 69
 
7.8%
R 35
 
4.0%
D 35
 
4.0%
Space Separator
ValueCountFrequency (%)
3535
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14158
80.0%
Common 3535
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2802
19.8%
a 2114
14.9%
s 1400
9.9%
t 1146
8.1%
m 772
 
5.5%
w 753
 
5.3%
n 723
 
5.1%
i 652
 
4.6%
f 583
 
4.1%
h 529
 
3.7%
Other values (15) 2684
19.0%
Common
ValueCountFrequency (%)
3535
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17693
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3535
20.0%
e 2802
15.8%
a 2114
11.9%
s 1400
 
7.9%
t 1146
 
6.5%
m 772
 
4.4%
w 753
 
4.3%
n 723
 
4.1%
i 652
 
3.7%
f 583
 
3.3%
Other values (16) 3213
18.2%

gfreight1b_qfreight2_ma
Text

MISSING 

Distinct8
Distinct (%)0.8%
Missing50
Missing (%)5.0%
Memory size71.2 KiB
2023-12-09T21:44:14.309111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length28
Median length19
Mean length17.88315789
Min length5

Characters and Unicode

Total characters16989
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOnce a month
2nd rowOnce a week
3rd rowLess than a few times a year
4th rowOnce a month
5th rowOnce a week
ValueCountFrequency (%)
a 1391
32.9%
times 633
15.0%
few 496
 
11.7%
month 316
 
7.5%
week 294
 
6.9%
year 285
 
6.7%
once 262
 
6.2%
less 181
 
4.3%
than 181
 
4.3%
several 137
 
3.2%
Other values (2) 55
 
1.3%
2023-12-09T21:44:14.607852image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3281
19.3%
e 2757
16.2%
a 1715
10.1%
t 1130
 
6.7%
s 1014
 
6.0%
m 949
 
5.6%
w 790
 
4.7%
n 759
 
4.5%
i 669
 
3.9%
f 515
 
3.0%
Other values (16) 3410
20.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12758
75.1%
Space Separator 3281
 
19.3%
Uppercase Letter 950
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2757
21.6%
a 1715
13.4%
t 1130
8.9%
s 1014
 
7.9%
m 949
 
7.4%
w 790
 
6.2%
n 759
 
5.9%
i 669
 
5.2%
f 515
 
4.0%
h 497
 
3.9%
Other values (9) 1963
15.4%
Uppercase Letter
ValueCountFrequency (%)
A 315
33.2%
O 262
27.6%
L 181
19.1%
S 137
14.4%
D 36
 
3.8%
R 19
 
2.0%
Space Separator
ValueCountFrequency (%)
3281
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13708
80.7%
Common 3281
 
19.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2757
20.1%
a 1715
12.5%
t 1130
 
8.2%
s 1014
 
7.4%
m 949
 
6.9%
w 790
 
5.8%
n 759
 
5.5%
i 669
 
4.9%
f 515
 
3.8%
h 497
 
3.6%
Other values (15) 2913
21.3%
Common
ValueCountFrequency (%)
3281
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16989
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3281
19.3%
e 2757
16.2%
a 1715
10.1%
t 1130
 
6.7%
s 1014
 
6.0%
m 949
 
5.6%
w 790
 
4.7%
n 759
 
4.5%
i 669
 
3.9%
f 515
 
3.0%
Other values (16) 3410
20.1%

gfreight1b_qfreight3_ma
Text

MISSING 

Distinct8
Distinct (%)0.9%
Missing142
Missing (%)14.2%
Memory size70.1 KiB
2023-12-09T21:44:14.774849image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length28
Median length28
Mean length21.22727273
Min length5

Characters and Unicode

Total characters18213
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLess than a few times a year
2nd rowLess than a few times a year
3rd rowLess than a few times a year
4th rowLess than a few times a year
5th rowA few times a year
ValueCountFrequency (%)
a 1365
30.1%
times 629
13.9%
few 571
12.6%
year 494
 
10.9%
less 442
 
9.8%
than 442
 
9.8%
once 165
 
3.6%
week 158
 
3.5%
month 142
 
3.1%
several 58
 
1.3%
Other values (2) 64
 
1.4%
2023-12-09T21:44:15.063728image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3672
20.2%
e 2811
15.4%
a 2255
12.4%
s 1552
8.5%
t 1213
 
6.7%
m 771
 
4.2%
n 749
 
4.1%
w 729
 
4.0%
i 654
 
3.6%
f 610
 
3.3%
Other values (16) 3197
17.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13683
75.1%
Space Separator 3672
 
20.2%
Uppercase Letter 858
 
4.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2811
20.5%
a 2255
16.5%
s 1552
11.3%
t 1213
8.9%
m 771
 
5.6%
n 749
 
5.5%
w 729
 
5.3%
i 654
 
4.8%
f 610
 
4.5%
h 584
 
4.3%
Other values (9) 1755
12.8%
Uppercase Letter
ValueCountFrequency (%)
L 442
51.5%
O 165
 
19.2%
A 129
 
15.0%
S 58
 
6.8%
R 39
 
4.5%
D 25
 
2.9%
Space Separator
ValueCountFrequency (%)
3672
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14541
79.8%
Common 3672
 
20.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2811
19.3%
a 2255
15.5%
s 1552
10.7%
t 1213
8.3%
m 771
 
5.3%
n 749
 
5.2%
w 729
 
5.0%
i 654
 
4.5%
f 610
 
4.2%
h 584
 
4.0%
Other values (15) 2613
18.0%
Common
ValueCountFrequency (%)
3672
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18213
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3672
20.2%
e 2811
15.4%
a 2255
12.4%
s 1552
8.5%
t 1213
 
6.7%
m 771
 
4.2%
n 749
 
4.1%
w 729
 
4.0%
i 654
 
3.6%
f 610
 
3.3%
Other values (16) 3197
17.6%

gfreight1b_qfreight4_ma
Text

MISSING 

Distinct8
Distinct (%)0.8%
Missing41
Missing (%)4.1%
Memory size70.8 KiB
2023-12-09T21:44:15.224048image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length28
Median length19
Mean length17.0729927
Min length5

Characters and Unicode

Total characters16373
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOnce a month
2nd rowA few times a month
3rd rowA few times a year
4th rowOnce a month
5th rowSeveral times a week
ValueCountFrequency (%)
a 1470
35.3%
times 649
15.6%
few 550
 
13.2%
month 461
 
11.1%
once 271
 
6.5%
year 237
 
5.7%
week 222
 
5.3%
several 99
 
2.4%
less 83
 
2.0%
than 83
 
2.0%
Other values (2) 39
 
0.9%
2023-12-09T21:44:15.496140image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3205
19.6%
e 2458
15.0%
a 1448
8.8%
t 1193
 
7.3%
m 1110
 
6.8%
s 828
 
5.1%
n 815
 
5.0%
w 772
 
4.7%
i 675
 
4.1%
f 563
 
3.4%
Other values (16) 3306
20.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12209
74.6%
Space Separator 3205
 
19.6%
Uppercase Letter 959
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2458
20.1%
a 1448
11.9%
t 1193
9.8%
m 1110
9.1%
s 828
 
6.8%
n 815
 
6.7%
w 772
 
6.3%
i 675
 
5.5%
f 563
 
4.6%
h 544
 
4.5%
Other values (9) 1803
14.8%
Uppercase Letter
ValueCountFrequency (%)
A 467
48.7%
O 271
28.3%
S 99
 
10.3%
L 83
 
8.7%
D 26
 
2.7%
R 13
 
1.4%
Space Separator
ValueCountFrequency (%)
3205
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13168
80.4%
Common 3205
 
19.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2458
18.7%
a 1448
11.0%
t 1193
9.1%
m 1110
8.4%
s 828
 
6.3%
n 815
 
6.2%
w 772
 
5.9%
i 675
 
5.1%
f 563
 
4.3%
h 544
 
4.1%
Other values (15) 2762
21.0%
Common
ValueCountFrequency (%)
3205
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16373
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3205
19.6%
e 2458
15.0%
a 1448
8.8%
t 1193
 
7.3%
m 1110
 
6.8%
s 828
 
5.1%
n 815
 
5.0%
w 772
 
4.7%
i 675
 
4.1%
f 563
 
3.4%
Other values (16) 3306
20.2%

qpackagedeliver
Text

MISSING 

Distinct9
Distinct (%)0.9%
Missing37
Missing (%)3.7%
Memory size70.2 KiB
2023-12-09T21:44:15.691212image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length67
Median length57
Mean length16.26687435
Min length5

Characters and Unicode

Total characters15665
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMy lobby
2nd rowMy lobby
3rd rowMy doorstep
4th rowMy lobby
5th rowMy doorstep
ValueCountFrequency (%)
my 740
26.7%
doorstep 429
15.5%
lobby 155
 
5.6%
access 116
 
4.2%
point 116
 
4.2%
an 112
 
4.0%
alternative 112
 
4.0%
i.e 112
 
4.0%
a 111
 
4.0%
doorman 108
 
3.9%
Other values (13) 660
23.8%
2023-12-09T21:44:16.019810image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1808
 
11.5%
o 1677
 
10.7%
e 1323
 
8.4%
r 1073
 
6.8%
y 949
 
6.1%
s 946
 
6.0%
t 928
 
5.9%
M 740
 
4.7%
a 715
 
4.6%
d 708
 
4.5%
Other values (25) 4798
30.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11928
76.1%
Space Separator 1808
 
11.5%
Uppercase Letter 1311
 
8.4%
Other Punctuation 394
 
2.5%
Close Punctuation 112
 
0.7%
Open Punctuation 112
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1677
14.1%
e 1323
11.1%
r 1073
9.0%
y 949
 
8.0%
s 946
 
7.9%
t 928
 
7.8%
a 715
 
6.0%
d 708
 
5.9%
p 592
 
5.0%
n 560
 
4.7%
Other values (12) 2457
20.6%
Uppercase Letter
ValueCountFrequency (%)
M 740
56.4%
A 285
 
21.7%
P 116
 
8.8%
U 58
 
4.4%
S 58
 
4.4%
O 45
 
3.4%
R 9
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 224
56.9%
, 116
29.4%
' 54
 
13.7%
Space Separator
ValueCountFrequency (%)
1808
100.0%
Close Punctuation
ValueCountFrequency (%)
) 112
100.0%
Open Punctuation
ValueCountFrequency (%)
( 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13239
84.5%
Common 2426
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1677
12.7%
e 1323
 
10.0%
r 1073
 
8.1%
y 949
 
7.2%
s 946
 
7.1%
t 928
 
7.0%
M 740
 
5.6%
a 715
 
5.4%
d 708
 
5.3%
p 592
 
4.5%
Other values (19) 3588
27.1%
Common
ValueCountFrequency (%)
1808
74.5%
. 224
 
9.2%
, 116
 
4.8%
) 112
 
4.6%
( 112
 
4.6%
' 54
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15665
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1808
 
11.5%
o 1677
 
10.7%
e 1323
 
8.4%
r 1073
 
6.8%
y 949
 
6.1%
s 946
 
6.0%
t 928
 
5.9%
M 740
 
4.7%
a 715
 
4.6%
d 708
 
4.5%
Other values (25) 4798
30.6%

qpostalstore
Text

MISSING 

Distinct6
Distinct (%)3.7%
Missing838
Missing (%)83.8%
Memory size37.2 KiB
2023-12-09T21:44:16.187973image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length10
Mean length12.04938272
Min length10

Characters and Unicode

Total characters1952
Distinct characters22
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10-20 blocks
2nd rowMore than 20 blocks
3rd row6-10 blocks
4th rowLess than 1 block
5th row1-2 blocks
ValueCountFrequency (%)
blocks 143
36.3%
3-5 51
 
12.9%
6-10 35
 
8.9%
than 35
 
8.9%
1-2 31
 
7.9%
less 19
 
4.8%
1 19
 
4.8%
block 19
 
4.8%
more 16
 
4.1%
20 16
 
4.1%
2023-12-09T21:44:16.479648image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
232
11.9%
s 181
9.3%
o 178
9.1%
b 162
 
8.3%
l 162
 
8.3%
c 162
 
8.3%
k 162
 
8.3%
- 127
 
6.5%
1 95
 
4.9%
0 71
 
3.6%
Other values (12) 420
21.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1198
61.4%
Decimal Number 360
 
18.4%
Space Separator 232
 
11.9%
Dash Punctuation 127
 
6.5%
Uppercase Letter 35
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 181
15.1%
o 178
14.9%
b 162
13.5%
l 162
13.5%
c 162
13.5%
k 162
13.5%
e 35
 
2.9%
t 35
 
2.9%
h 35
 
2.9%
a 35
 
2.9%
Other values (2) 51
 
4.3%
Decimal Number
ValueCountFrequency (%)
1 95
26.4%
0 71
19.7%
2 57
15.8%
3 51
14.2%
5 51
14.2%
6 35
 
9.7%
Uppercase Letter
ValueCountFrequency (%)
L 19
54.3%
M 16
45.7%
Space Separator
ValueCountFrequency (%)
232
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1233
63.2%
Common 719
36.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 181
14.7%
o 178
14.4%
b 162
13.1%
l 162
13.1%
c 162
13.1%
k 162
13.1%
e 35
 
2.8%
t 35
 
2.8%
h 35
 
2.8%
a 35
 
2.8%
Other values (4) 86
7.0%
Common
ValueCountFrequency (%)
232
32.3%
- 127
17.7%
1 95
13.2%
0 71
 
9.9%
2 57
 
7.9%
3 51
 
7.1%
5 51
 
7.1%
6 35
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
232
11.9%
s 181
9.3%
o 178
9.1%
b 162
 
8.3%
l 162
 
8.3%
c 162
 
8.3%
k 162
 
8.3%
- 127
 
6.5%
1 95
 
4.9%
0 71
 
3.6%
Other values (12) 420
21.5%

qsubwayservice
Text

MISSING 

Distinct4
Distinct (%)0.4%
Missing82
Missing (%)8.2%
Memory size66.5 KiB
2023-12-09T21:44:16.654882image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length16
Median length13
Mean length14.19716776
Min length7

Characters and Unicode

Total characters13033
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGetting worse
2nd rowGetting worse
3rd rowGetting worse
4th rowGetting worse
5th rowStaying the same
ValueCountFrequency (%)
getting 580
26.7%
worse 477
22.0%
staying 336
15.5%
the 336
15.5%
same 336
15.5%
better 103
 
4.7%
refused 2
 
0.1%
2023-12-09T21:44:16.940112image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2038
15.6%
e 1939
14.9%
1252
9.6%
i 916
 
7.0%
n 916
 
7.0%
g 916
 
7.0%
s 815
 
6.3%
a 672
 
5.2%
r 580
 
4.5%
G 580
 
4.5%
Other values (11) 2409
18.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10863
83.3%
Space Separator 1252
 
9.6%
Uppercase Letter 918
 
7.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2038
18.8%
e 1939
17.8%
i 916
8.4%
n 916
8.4%
g 916
8.4%
s 815
 
7.5%
a 672
 
6.2%
r 580
 
5.3%
o 477
 
4.4%
w 477
 
4.4%
Other values (7) 1117
10.3%
Uppercase Letter
ValueCountFrequency (%)
G 580
63.2%
S 336
36.6%
R 2
 
0.2%
Space Separator
ValueCountFrequency (%)
1252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11781
90.4%
Common 1252
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2038
17.3%
e 1939
16.5%
i 916
7.8%
n 916
7.8%
g 916
7.8%
s 815
 
6.9%
a 672
 
5.7%
r 580
 
4.9%
G 580
 
4.9%
o 477
 
4.0%
Other values (10) 1932
16.4%
Common
ValueCountFrequency (%)
1252
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13033
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 2038
15.6%
e 1939
14.9%
1252
9.6%
i 916
 
7.0%
n 916
 
7.0%
g 916
 
7.0%
s 815
 
6.3%
a 672
 
5.2%
r 580
 
4.5%
G 580
 
4.5%
Other values (11) 2409
18.5%

qsubwayimpact
Text

MISSING 

Distinct3
Distinct (%)0.5%
Missing428
Missing (%)42.8%
Memory size63.2 KiB
2023-12-09T21:44:17.114575image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length32
Median length32
Mean length32
Min length32

Characters and Unicode

Total characters18304
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI use the subway the same amount
2nd rowI use the subway the same amount
3rd rowI use the subway the same amount
4th rowI use the subway the same amount
5th rowI use the subway the same amount
ValueCountFrequency (%)
the 853
23.0%
i 572
15.4%
use 572
15.4%
subway 572
15.4%
frequently 291
 
7.8%
same 281
 
7.6%
amount 281
 
7.6%
less 217
 
5.8%
more 74
 
2.0%
2023-12-09T21:44:17.400669image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3141
17.2%
e 2579
14.1%
s 1859
10.2%
u 1716
9.4%
t 1425
7.8%
a 1134
 
6.2%
y 863
 
4.7%
h 853
 
4.7%
m 636
 
3.5%
n 572
 
3.1%
Other values (8) 3526
19.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14591
79.7%
Space Separator 3141
 
17.2%
Uppercase Letter 572
 
3.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2579
17.7%
s 1859
12.7%
u 1716
11.8%
t 1425
9.8%
a 1134
7.8%
y 863
 
5.9%
h 853
 
5.8%
m 636
 
4.4%
n 572
 
3.9%
w 572
 
3.9%
Other values (6) 2382
16.3%
Space Separator
ValueCountFrequency (%)
3141
100.0%
Uppercase Letter
ValueCountFrequency (%)
I 572
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15163
82.8%
Common 3141
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2579
17.0%
s 1859
12.3%
u 1716
11.3%
t 1425
9.4%
a 1134
 
7.5%
y 863
 
5.7%
h 853
 
5.6%
m 636
 
4.2%
n 572
 
3.8%
I 572
 
3.8%
Other values (7) 2954
19.5%
Common
ValueCountFrequency (%)
3141
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3141
17.2%
e 2579
14.1%
s 1859
10.2%
u 1716
9.4%
t 1425
7.8%
a 1134
 
6.2%
y 863
 
4.7%
h 853
 
4.7%
m 636
 
3.5%
n 572
 
3.1%
Other values (8) 3526
19.3%

qtransportnosubway01
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing783
Missing (%)78.3%
Memory size37.2 KiB
2023-12-09T21:44:17.530460image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.377880184
Min length2

Characters and Unicode

Total characters516
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 135
62.2%
yes 82
37.8%
2023-12-09T21:44:17.777448image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 135
26.2%
o 135
26.2%
Y 82
15.9%
e 82
15.9%
s 82
15.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 299
57.9%
Uppercase Letter 217
42.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 135
45.2%
e 82
27.4%
s 82
27.4%
Uppercase Letter
ValueCountFrequency (%)
N 135
62.2%
Y 82
37.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 516
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 135
26.2%
o 135
26.2%
Y 82
15.9%
e 82
15.9%
s 82
15.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 516
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 135
26.2%
o 135
26.2%
Y 82
15.9%
e 82
15.9%
s 82
15.9%

qtransportnosubway02
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing783
Missing (%)78.3%
Memory size37.2 KiB
2023-12-09T21:44:17.901447image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.32718894
Min length2

Characters and Unicode

Total characters505
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowYes
3rd rowYes
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 146
67.3%
yes 71
32.7%
2023-12-09T21:44:18.144893image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 146
28.9%
o 146
28.9%
Y 71
14.1%
e 71
14.1%
s 71
14.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 288
57.0%
Uppercase Letter 217
43.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 146
50.7%
e 71
24.7%
s 71
24.7%
Uppercase Letter
ValueCountFrequency (%)
N 146
67.3%
Y 71
32.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 505
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 146
28.9%
o 146
28.9%
Y 71
14.1%
e 71
14.1%
s 71
14.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 505
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 146
28.9%
o 146
28.9%
Y 71
14.1%
e 71
14.1%
s 71
14.1%

qtransportnosubway03
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing783
Missing (%)78.3%
Memory size37.2 KiB
2023-12-09T21:44:18.274576image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.373271889
Min length2

Characters and Unicode

Total characters515
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 136
62.7%
yes 81
37.3%
2023-12-09T21:44:18.522331image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 136
26.4%
o 136
26.4%
Y 81
15.7%
e 81
15.7%
s 81
15.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 298
57.9%
Uppercase Letter 217
42.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 136
45.6%
e 81
27.2%
s 81
27.2%
Uppercase Letter
ValueCountFrequency (%)
N 136
62.7%
Y 81
37.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 515
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 136
26.4%
o 136
26.4%
Y 81
15.7%
e 81
15.7%
s 81
15.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 515
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 136
26.4%
o 136
26.4%
Y 81
15.7%
e 81
15.7%
s 81
15.7%

qtransportnosubway04
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing783
Missing (%)78.3%
Memory size37.1 KiB
2023-12-09T21:44:18.634255image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.138248848
Min length2

Characters and Unicode

Total characters464
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 187
86.2%
yes 30
 
13.8%
2023-12-09T21:44:18.863880image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 187
40.3%
o 187
40.3%
Y 30
 
6.5%
e 30
 
6.5%
s 30
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 247
53.2%
Uppercase Letter 217
46.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 187
75.7%
e 30
 
12.1%
s 30
 
12.1%
Uppercase Letter
ValueCountFrequency (%)
N 187
86.2%
Y 30
 
13.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 464
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 187
40.3%
o 187
40.3%
Y 30
 
6.5%
e 30
 
6.5%
s 30
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 464
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 187
40.3%
o 187
40.3%
Y 30
 
6.5%
e 30
 
6.5%
s 30
 
6.5%

qtransportnosubway05
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing783
Missing (%)78.3%
Memory size37.1 KiB
2023-12-09T21:44:18.975005image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.110599078
Min length2

Characters and Unicode

Total characters458
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 193
88.9%
yes 24
 
11.1%
2023-12-09T21:44:19.195200image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 193
42.1%
o 193
42.1%
Y 24
 
5.2%
e 24
 
5.2%
s 24
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 241
52.6%
Uppercase Letter 217
47.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 193
80.1%
e 24
 
10.0%
s 24
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
N 193
88.9%
Y 24
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 458
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 193
42.1%
o 193
42.1%
Y 24
 
5.2%
e 24
 
5.2%
s 24
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 458
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 193
42.1%
o 193
42.1%
Y 24
 
5.2%
e 24
 
5.2%
s 24
 
5.2%

qtransportnosubway06
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing783
Missing (%)78.3%
Memory size37.1 KiB
2023-12-09T21:44:19.304533image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.050691244
Min length2

Characters and Unicode

Total characters445
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowYes
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 206
94.9%
yes 11
 
5.1%
2023-12-09T21:44:19.523807image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 206
46.3%
o 206
46.3%
Y 11
 
2.5%
e 11
 
2.5%
s 11
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 228
51.2%
Uppercase Letter 217
48.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 206
90.4%
e 11
 
4.8%
s 11
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
N 206
94.9%
Y 11
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 445
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 206
46.3%
o 206
46.3%
Y 11
 
2.5%
e 11
 
2.5%
s 11
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 445
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 206
46.3%
o 206
46.3%
Y 11
 
2.5%
e 11
 
2.5%
s 11
 
2.5%

qtransportnosubway07
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing783
Missing (%)78.3%
Memory size37.1 KiB
2023-12-09T21:44:19.631533image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.023041475
Min length2

Characters and Unicode

Total characters439
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 212
97.7%
yes 5
 
2.3%
2023-12-09T21:44:19.849109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 212
48.3%
o 212
48.3%
Y 5
 
1.1%
e 5
 
1.1%
s 5
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 222
50.6%
Uppercase Letter 217
49.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 212
95.5%
e 5
 
2.3%
s 5
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
N 212
97.7%
Y 5
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 439
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 212
48.3%
o 212
48.3%
Y 5
 
1.1%
e 5
 
1.1%
s 5
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 439
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 212
48.3%
o 212
48.3%
Y 5
 
1.1%
e 5
 
1.1%
s 5
 
1.1%

qtransportnosubway08
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing783
Missing (%)78.3%
Memory size37.1 KiB
2023-12-09T21:44:19.957922image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.023041475
Min length2

Characters and Unicode

Total characters439
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 212
97.7%
yes 5
 
2.3%
2023-12-09T21:44:20.181003image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 212
48.3%
o 212
48.3%
Y 5
 
1.1%
e 5
 
1.1%
s 5
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 222
50.6%
Uppercase Letter 217
49.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 212
95.5%
e 5
 
2.3%
s 5
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
N 212
97.7%
Y 5
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 439
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 212
48.3%
o 212
48.3%
Y 5
 
1.1%
e 5
 
1.1%
s 5
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 439
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 212
48.3%
o 212
48.3%
Y 5
 
1.1%
e 5
 
1.1%
s 5
 
1.1%

qtransportnosubway09
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing783
Missing (%)78.3%
Memory size37.1 KiB
2023-12-09T21:44:20.293667image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.041474654
Min length2

Characters and Unicode

Total characters443
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 208
95.9%
yes 9
 
4.1%
2023-12-09T21:44:20.515312image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 208
47.0%
o 208
47.0%
Y 9
 
2.0%
e 9
 
2.0%
s 9
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 226
51.0%
Uppercase Letter 217
49.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 208
92.0%
e 9
 
4.0%
s 9
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
N 208
95.9%
Y 9
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 443
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 208
47.0%
o 208
47.0%
Y 9
 
2.0%
e 9
 
2.0%
s 9
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 443
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 208
47.0%
o 208
47.0%
Y 9
 
2.0%
e 9
 
2.0%
s 9
 
2.0%

qtransportnosubway10
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing783
Missing (%)78.3%
Memory size37.1 KiB
2023-12-09T21:44:20.622123image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.004608295
Min length2

Characters and Unicode

Total characters435
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 216
99.5%
yes 1
 
0.5%
2023-12-09T21:44:20.838999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 216
49.7%
o 216
49.7%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 218
50.1%
Uppercase Letter 217
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 216
99.1%
e 1
 
0.5%
s 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 216
99.5%
Y 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 435
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 216
49.7%
o 216
49.7%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 435
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 216
49.7%
o 216
49.7%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

qtransportnosubway11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing783
Missing (%)78.3%
Memory size37.1 KiB
2023-12-09T21:44:20.940281image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters434
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 217
100.0%
2023-12-09T21:44:21.145138image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 217
50.0%
o 217
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 217
50.0%
Lowercase Letter 217
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 217
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 217
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 434
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 217
50.0%
o 217
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 434
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 217
50.0%
o 217
50.0%

qbusservice
Text

MISSING 

Distinct4
Distinct (%)0.5%
Missing149
Missing (%)14.9%
Memory size64.5 KiB
2023-12-09T21:44:21.318628image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length16
Median length16
Mean length14.83548766
Min length7

Characters and Unicode

Total characters12625
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGetting better
2nd rowStaying the same
3rd rowStaying the same
4th rowGetting worse
5th rowGetting worse
ValueCountFrequency (%)
staying 472
21.7%
the 472
21.7%
same 472
21.7%
getting 376
17.3%
worse 212
9.8%
better 164
 
7.6%
refused 3
 
0.1%
2023-12-09T21:44:21.616789image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2024
16.0%
e 1866
14.8%
1320
10.5%
a 944
7.5%
i 848
 
6.7%
n 848
 
6.7%
g 848
 
6.7%
s 687
 
5.4%
m 472
 
3.7%
S 472
 
3.7%
Other values (11) 2296
18.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10454
82.8%
Space Separator 1320
 
10.5%
Uppercase Letter 851
 
6.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2024
19.4%
e 1866
17.8%
a 944
9.0%
i 848
8.1%
n 848
8.1%
g 848
8.1%
s 687
 
6.6%
m 472
 
4.5%
h 472
 
4.5%
y 472
 
4.5%
Other values (7) 973
9.3%
Uppercase Letter
ValueCountFrequency (%)
S 472
55.5%
G 376
44.2%
R 3
 
0.4%
Space Separator
ValueCountFrequency (%)
1320
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11305
89.5%
Common 1320
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2024
17.9%
e 1866
16.5%
a 944
8.4%
i 848
7.5%
n 848
7.5%
g 848
7.5%
s 687
 
6.1%
m 472
 
4.2%
S 472
 
4.2%
h 472
 
4.2%
Other values (10) 1824
16.1%
Common
ValueCountFrequency (%)
1320
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12625
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 2024
16.0%
e 1866
14.8%
1320
10.5%
a 944
7.5%
i 848
 
6.7%
n 848
 
6.7%
g 848
 
6.7%
s 687
 
5.4%
m 472
 
3.7%
S 472
 
3.7%
Other values (11) 2296
18.2%

qbusimpact
Text

MISSING 

Distinct3
Distinct (%)0.8%
Missing631
Missing (%)63.1%
Memory size51.2 KiB
2023-12-09T21:44:21.789067image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length30
Mean length30
Min length30

Characters and Unicode

Total characters11070
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI take the bus the same amount
2nd rowI take the bus the same amount
3rd rowI take the bus less frequently
4th rowI take the bus the same amount
5th rowI take the bus the same amount
ValueCountFrequency (%)
the 537
22.5%
i 369
15.5%
take 369
15.5%
bus 369
15.5%
frequently 201
 
8.4%
same 168
 
7.1%
amount 168
 
7.1%
less 126
 
5.3%
more 75
 
3.1%
2023-12-09T21:44:22.079458image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2013
18.2%
e 1677
15.1%
t 1275
11.5%
s 789
 
7.1%
u 738
 
6.7%
a 705
 
6.4%
h 537
 
4.9%
m 411
 
3.7%
n 369
 
3.3%
I 369
 
3.3%
Other values (8) 2187
19.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8688
78.5%
Space Separator 2013
 
18.2%
Uppercase Letter 369
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1677
19.3%
t 1275
14.7%
s 789
9.1%
u 738
8.5%
a 705
8.1%
h 537
 
6.2%
m 411
 
4.7%
n 369
 
4.2%
b 369
 
4.2%
k 369
 
4.2%
Other values (6) 1449
16.7%
Space Separator
ValueCountFrequency (%)
2013
100.0%
Uppercase Letter
ValueCountFrequency (%)
I 369
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9057
81.8%
Common 2013
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1677
18.5%
t 1275
14.1%
s 789
8.7%
u 738
8.1%
a 705
 
7.8%
h 537
 
5.9%
m 411
 
4.5%
n 369
 
4.1%
I 369
 
4.1%
b 369
 
4.1%
Other values (7) 1818
20.1%
Common
ValueCountFrequency (%)
2013
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11070
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2013
18.2%
e 1677
15.1%
t 1275
11.5%
s 789
 
7.1%
u 738
 
6.7%
a 705
 
6.4%
h 537
 
4.9%
m 411
 
3.7%
n 369
 
3.3%
I 369
 
3.3%
Other values (8) 2187
19.8%

qtransportnobus01
Text

MISSING 

Distinct2
Distinct (%)6.1%
Missing967
Missing (%)96.7%
Memory size32.3 KiB
2023-12-09T21:44:22.210882image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.363636364
Min length2

Characters and Unicode

Total characters78
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowNo
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 21
63.6%
yes 12
36.4%
2023-12-09T21:44:22.450328image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 21
26.9%
o 21
26.9%
Y 12
15.4%
e 12
15.4%
s 12
15.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 45
57.7%
Uppercase Letter 33
42.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 21
46.7%
e 12
26.7%
s 12
26.7%
Uppercase Letter
ValueCountFrequency (%)
N 21
63.6%
Y 12
36.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 78
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 21
26.9%
o 21
26.9%
Y 12
15.4%
e 12
15.4%
s 12
15.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 21
26.9%
o 21
26.9%
Y 12
15.4%
e 12
15.4%
s 12
15.4%

qtransportnobus02
Text

MISSING 

Distinct2
Distinct (%)6.1%
Missing967
Missing (%)96.7%
Memory size32.3 KiB
2023-12-09T21:44:22.589520image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.484848485
Min length2

Characters and Unicode

Total characters82
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowNo
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 17
51.5%
yes 16
48.5%
2023-12-09T21:44:22.848876image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 17
20.7%
o 17
20.7%
Y 16
19.5%
e 16
19.5%
s 16
19.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 49
59.8%
Uppercase Letter 33
40.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 17
34.7%
e 16
32.7%
s 16
32.7%
Uppercase Letter
ValueCountFrequency (%)
N 17
51.5%
Y 16
48.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 82
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 17
20.7%
o 17
20.7%
Y 16
19.5%
e 16
19.5%
s 16
19.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 17
20.7%
o 17
20.7%
Y 16
19.5%
e 16
19.5%
s 16
19.5%

qtransportnobus03
Text

MISSING 

Distinct2
Distinct (%)6.1%
Missing967
Missing (%)96.7%
Memory size32.3 KiB
2023-12-09T21:44:22.982565image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.393939394
Min length2

Characters and Unicode

Total characters79
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 20
60.6%
yes 13
39.4%
2023-12-09T21:44:23.222490image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 20
25.3%
o 20
25.3%
Y 13
16.5%
e 13
16.5%
s 13
16.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 46
58.2%
Uppercase Letter 33
41.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 20
43.5%
e 13
28.3%
s 13
28.3%
Uppercase Letter
ValueCountFrequency (%)
N 20
60.6%
Y 13
39.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 79
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 20
25.3%
o 20
25.3%
Y 13
16.5%
e 13
16.5%
s 13
16.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 20
25.3%
o 20
25.3%
Y 13
16.5%
e 13
16.5%
s 13
16.5%

qtransportnobus04
Text

MISSING 

Distinct2
Distinct (%)6.1%
Missing967
Missing (%)96.7%
Memory size32.3 KiB
2023-12-09T21:44:23.341183image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.212121212
Min length2

Characters and Unicode

Total characters73
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 26
78.8%
yes 7
 
21.2%
2023-12-09T21:44:23.571463image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 26
35.6%
o 26
35.6%
Y 7
 
9.6%
e 7
 
9.6%
s 7
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 40
54.8%
Uppercase Letter 33
45.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 26
65.0%
e 7
 
17.5%
s 7
 
17.5%
Uppercase Letter
ValueCountFrequency (%)
N 26
78.8%
Y 7
 
21.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 73
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 26
35.6%
o 26
35.6%
Y 7
 
9.6%
e 7
 
9.6%
s 7
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 26
35.6%
o 26
35.6%
Y 7
 
9.6%
e 7
 
9.6%
s 7
 
9.6%

qtransportnobus05
Text

MISSING 

Distinct2
Distinct (%)6.1%
Missing967
Missing (%)96.7%
Memory size32.2 KiB
2023-12-09T21:44:23.683491image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.121212121
Min length2

Characters and Unicode

Total characters70
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 29
87.9%
yes 4
 
12.1%
2023-12-09T21:44:23.908746image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 29
41.4%
o 29
41.4%
Y 4
 
5.7%
e 4
 
5.7%
s 4
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 37
52.9%
Uppercase Letter 33
47.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 29
78.4%
e 4
 
10.8%
s 4
 
10.8%
Uppercase Letter
ValueCountFrequency (%)
N 29
87.9%
Y 4
 
12.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 70
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 29
41.4%
o 29
41.4%
Y 4
 
5.7%
e 4
 
5.7%
s 4
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 29
41.4%
o 29
41.4%
Y 4
 
5.7%
e 4
 
5.7%
s 4
 
5.7%

qtransportnobus06
Text

MISSING 

Distinct2
Distinct (%)6.1%
Missing967
Missing (%)96.7%
Memory size32.2 KiB
2023-12-09T21:44:24.015863image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.03030303
Min length2

Characters and Unicode

Total characters67
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 32
97.0%
yes 1
 
3.0%
2023-12-09T21:44:24.242322image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 32
47.8%
o 32
47.8%
Y 1
 
1.5%
e 1
 
1.5%
s 1
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34
50.7%
Uppercase Letter 33
49.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 32
94.1%
e 1
 
2.9%
s 1
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
N 32
97.0%
Y 1
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 67
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 32
47.8%
o 32
47.8%
Y 1
 
1.5%
e 1
 
1.5%
s 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 32
47.8%
o 32
47.8%
Y 1
 
1.5%
e 1
 
1.5%
s 1
 
1.5%

qtransportnobus07
Text

MISSING 

Distinct2
Distinct (%)6.1%
Missing967
Missing (%)96.7%
Memory size32.2 KiB
2023-12-09T21:44:24.355038image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.151515152
Min length2

Characters and Unicode

Total characters71
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 28
84.8%
yes 5
 
15.2%
2023-12-09T21:44:24.579938image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 28
39.4%
o 28
39.4%
Y 5
 
7.0%
e 5
 
7.0%
s 5
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 38
53.5%
Uppercase Letter 33
46.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 28
73.7%
e 5
 
13.2%
s 5
 
13.2%
Uppercase Letter
ValueCountFrequency (%)
N 28
84.8%
Y 5
 
15.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 71
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 28
39.4%
o 28
39.4%
Y 5
 
7.0%
e 5
 
7.0%
s 5
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 28
39.4%
o 28
39.4%
Y 5
 
7.0%
e 5
 
7.0%
s 5
 
7.0%

qtransportnobus08
Text

MISSING 

Distinct2
Distinct (%)6.1%
Missing967
Missing (%)96.7%
Memory size32.2 KiB
2023-12-09T21:44:24.688250image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.03030303
Min length2

Characters and Unicode

Total characters67
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 32
97.0%
yes 1
 
3.0%
2023-12-09T21:44:24.913107image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 32
47.8%
o 32
47.8%
Y 1
 
1.5%
e 1
 
1.5%
s 1
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34
50.7%
Uppercase Letter 33
49.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 32
94.1%
e 1
 
2.9%
s 1
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
N 32
97.0%
Y 1
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 67
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 32
47.8%
o 32
47.8%
Y 1
 
1.5%
e 1
 
1.5%
s 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 32
47.8%
o 32
47.8%
Y 1
 
1.5%
e 1
 
1.5%
s 1
 
1.5%

qtransportnobus09
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)3.0%
Missing967
Missing (%)96.7%
Memory size32.2 KiB
2023-12-09T21:44:25.014441image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters66
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 33
100.0%
2023-12-09T21:44:25.224062image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 33
50.0%
o 33
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 33
50.0%
Lowercase Letter 33
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 33
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 66
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 33
50.0%
o 33
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 33
50.0%
o 33
50.0%

qtransportnobus10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)3.0%
Missing967
Missing (%)96.7%
Memory size32.2 KiB
2023-12-09T21:44:25.324861image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters66
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 33
100.0%
2023-12-09T21:44:25.542420image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 33
50.0%
o 33
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 33
50.0%
Lowercase Letter 33
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 33
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 66
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 33
50.0%
o 33
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 33
50.0%
o 33
50.0%

qtransportnobus11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)3.0%
Missing967
Missing (%)96.7%
Memory size32.2 KiB
2023-12-09T21:44:25.645459image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters66
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 33
100.0%
2023-12-09T21:44:25.857111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 33
50.0%
o 33
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 33
50.0%
Lowercase Letter 33
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 33
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 66
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 33
50.0%
o 33
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 33
50.0%
o 33
50.0%

qautovehiclefam
Text

MISSING 

Distinct5
Distinct (%)0.5%
Missing31
Missing (%)3.1%
Memory size71.4 KiB
2023-12-09T21:44:26.021774image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length17
Mean length17.28895769
Min length7

Characters and Unicode

Total characters16753
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowSomewhat familiar
2nd rowNot very familiar
3rd rowNot very familiar
4th rowSomewhat familiar
5th rowSomewhat familiar
ValueCountFrequency (%)
familiar 968
34.9%
not 559
20.2%
very 348
 
12.5%
somewhat 343
 
12.4%
at 277
 
10.0%
all 277
 
10.0%
refused 1
 
< 0.1%
2023-12-09T21:44:26.302457image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2833
16.9%
i 1936
11.6%
1804
10.8%
l 1522
9.1%
r 1316
7.9%
m 1311
7.8%
t 1179
7.0%
f 969
 
5.8%
o 902
 
5.4%
e 693
 
4.1%
Other values (11) 2288
13.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13980
83.4%
Space Separator 1804
 
10.8%
Uppercase Letter 969
 
5.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2833
20.3%
i 1936
13.8%
l 1522
10.9%
r 1316
9.4%
m 1311
9.4%
t 1179
8.4%
f 969
 
6.9%
o 902
 
6.5%
e 693
 
5.0%
y 348
 
2.5%
Other values (6) 971
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
N 559
57.7%
S 343
35.4%
V 66
 
6.8%
R 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1804
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14949
89.2%
Common 1804
 
10.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2833
19.0%
i 1936
13.0%
l 1522
10.2%
r 1316
8.8%
m 1311
8.8%
t 1179
7.9%
f 969
 
6.5%
o 902
 
6.0%
e 693
 
4.6%
N 559
 
3.7%
Other values (10) 1729
11.6%
Common
ValueCountFrequency (%)
1804
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16753
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2833
16.9%
i 1936
11.6%
1804
10.8%
l 1522
9.1%
r 1316
7.9%
m 1311
7.8%
t 1179
7.0%
f 969
 
5.8%
o 902
 
5.4%
e 693
 
4.1%
Other values (11) 2288
13.7%

qautovehiclewill
Text

MISSING 

Distinct4
Distinct (%)0.4%
Missing35
Missing (%)3.5%
Memory size70.3 KiB
2023-12-09T21:44:26.467521image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length16
Mean length16.35647668
Min length12

Characters and Unicode

Total characters15784
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot very willing
2nd rowNot very willing
3rd rowSomewhat willing
4th rowSomewhat willing
5th rowNot very willing
ValueCountFrequency (%)
willing 965
32.8%
not 634
21.5%
at 378
 
12.8%
all 378
 
12.8%
very 359
 
12.2%
somewhat 228
 
7.7%
2023-12-09T21:44:26.748172image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 2686
17.0%
1977
12.5%
i 1930
12.2%
t 1240
7.9%
w 1193
7.6%
a 984
 
6.2%
g 965
 
6.1%
n 965
 
6.1%
o 862
 
5.5%
N 634
 
4.0%
Other values (8) 2348
14.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12842
81.4%
Space Separator 1977
 
12.5%
Uppercase Letter 965
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 2686
20.9%
i 1930
15.0%
t 1240
9.7%
w 1193
9.3%
a 984
 
7.7%
g 965
 
7.5%
n 965
 
7.5%
o 862
 
6.7%
e 587
 
4.6%
r 359
 
2.8%
Other values (4) 1071
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
N 634
65.7%
S 228
 
23.6%
V 103
 
10.7%
Space Separator
ValueCountFrequency (%)
1977
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13807
87.5%
Common 1977
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 2686
19.5%
i 1930
14.0%
t 1240
9.0%
w 1193
8.6%
a 984
 
7.1%
g 965
 
7.0%
n 965
 
7.0%
o 862
 
6.2%
N 634
 
4.6%
e 587
 
4.3%
Other values (7) 1761
12.8%
Common
ValueCountFrequency (%)
1977
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15784
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 2686
17.0%
1977
12.5%
i 1930
12.2%
t 1240
7.9%
w 1193
7.6%
a 984
 
6.2%
g 965
 
6.1%
n 965
 
6.1%
o 862
 
5.5%
N 634
 
4.0%
Other values (8) 2348
14.9%

qautovehiclesafe
Text

Distinct7
Distinct (%)0.7%
Missing2
Missing (%)0.2%
Memory size93.6 KiB
2023-12-09T21:44:26.953532image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length49
Median length41
Mean length38.8496994
Min length5

Characters and Unicode

Total characters38772
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNeither more nor less safe than standard vehicles
2nd rowSomewhat less safe than standard vehicles
3rd rowNeither more nor less safe than standard vehicles
4th rowSomewhat less safe than standard vehicles
5th rowSomewhat less safe than standard vehicles
ValueCountFrequency (%)
than 962
16.1%
standard 962
16.1%
vehicles 962
16.1%
less 741
12.4%
safe 741
12.4%
somewhat 405
6.8%
much 376
 
6.3%
safer 221
 
3.7%
neither 181
 
3.0%
more 181
 
3.0%
Other values (4) 235
 
3.9%
2023-12-09T21:44:27.287877image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4969
12.8%
e 4593
11.8%
s 4368
11.3%
a 4253
11.0%
h 2904
 
7.5%
t 2546
 
6.6%
n 2141
 
5.5%
d 1924
 
5.0%
r 1744
 
4.5%
l 1703
 
4.4%
Other values (15) 7627
19.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32769
84.5%
Space Separator 4969
 
12.8%
Uppercase Letter 1016
 
2.6%
Other Punctuation 18
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4593
14.0%
s 4368
13.3%
a 4253
13.0%
h 2904
8.9%
t 2546
7.8%
n 2141
6.5%
d 1924
 
5.9%
r 1744
 
5.3%
l 1703
 
5.2%
c 1338
 
4.1%
Other values (7) 5255
16.0%
Uppercase Letter
ValueCountFrequency (%)
S 405
39.9%
M 376
37.0%
N 181
17.8%
O 18
 
1.8%
D 18
 
1.8%
K 18
 
1.8%
Space Separator
ValueCountFrequency (%)
4969
100.0%
Other Punctuation
ValueCountFrequency (%)
' 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 33785
87.1%
Common 4987
 
12.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4593
13.6%
s 4368
12.9%
a 4253
12.6%
h 2904
8.6%
t 2546
7.5%
n 2141
 
6.3%
d 1924
 
5.7%
r 1744
 
5.2%
l 1703
 
5.0%
c 1338
 
4.0%
Other values (13) 6271
18.6%
Common
ValueCountFrequency (%)
4969
99.6%
' 18
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38772
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4969
12.8%
e 4593
11.8%
s 4368
11.3%
a 4253
11.0%
h 2904
 
7.5%
t 2546
 
6.6%
n 2141
 
5.5%
d 1924
 
5.0%
r 1744
 
4.5%
l 1703
 
4.4%
Other values (15) 7627
19.7%

qmarried
Text

Distinct6
Distinct (%)0.6%
Missing4
Missing (%)0.4%
Memory size63.9 KiB
2023-12-09T21:44:27.480080image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length33
Median length8
Mean length8.463855422
Min length6

Characters and Unicode

Total characters8430
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSingle
2nd rowMarried
3rd rowDivorced
4th rowSingle
5th rowMarried
ValueCountFrequency (%)
single 418
32.8%
married 398
31.2%
living 70
 
5.5%
in 70
 
5.5%
a 70
 
5.5%
committed 70
 
5.5%
partnership 70
 
5.5%
divorced 56
 
4.4%
widowed 48
 
3.8%
refused 6
 
0.5%
2023-12-09T21:44:27.803826image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1270
15.1%
e 1072
12.7%
r 992
11.8%
n 628
 
7.4%
d 626
 
7.4%
a 538
 
6.4%
g 488
 
5.8%
S 418
 
5.0%
l 418
 
5.0%
M 398
 
4.7%
Other values (16) 1582
18.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7154
84.9%
Uppercase Letter 996
 
11.8%
Space Separator 280
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1270
17.8%
e 1072
15.0%
r 992
13.9%
n 628
8.8%
d 626
8.8%
a 538
7.5%
g 488
 
6.8%
l 418
 
5.8%
t 210
 
2.9%
o 174
 
2.4%
Other values (9) 738
10.3%
Uppercase Letter
ValueCountFrequency (%)
S 418
42.0%
M 398
40.0%
L 70
 
7.0%
D 56
 
5.6%
W 48
 
4.8%
R 6
 
0.6%
Space Separator
ValueCountFrequency (%)
280
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8150
96.7%
Common 280
 
3.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 1270
15.6%
e 1072
13.2%
r 992
12.2%
n 628
7.7%
d 626
7.7%
a 538
6.6%
g 488
 
6.0%
S 418
 
5.1%
l 418
 
5.1%
M 398
 
4.9%
Other values (15) 1302
16.0%
Common
ValueCountFrequency (%)
280
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8430
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 1270
15.1%
e 1072
12.7%
r 992
11.8%
n 628
 
7.4%
d 626
 
7.4%
a 538
 
6.4%
g 488
 
5.8%
S 418
 
5.0%
l 418
 
5.0%
M 398
 
4.7%
Other values (16) 1582
18.8%

qwelfare1
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.8 KiB
2023-12-09T21:44:27.925152image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.085170341
Min length2

Characters and Unicode

Total characters2081
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 913
91.5%
yes 85
 
8.5%
2023-12-09T21:44:28.161431image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 913
43.9%
o 913
43.9%
Y 85
 
4.1%
e 85
 
4.1%
s 85
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1083
52.0%
Uppercase Letter 998
48.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 913
84.3%
e 85
 
7.8%
s 85
 
7.8%
Uppercase Letter
ValueCountFrequency (%)
N 913
91.5%
Y 85
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 2081
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 913
43.9%
o 913
43.9%
Y 85
 
4.1%
e 85
 
4.1%
s 85
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2081
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 913
43.9%
o 913
43.9%
Y 85
 
4.1%
e 85
 
4.1%
s 85
 
4.1%

qwelfare2
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.8 KiB
2023-12-09T21:44:28.279119image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.066132265
Min length2

Characters and Unicode

Total characters2062
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 932
93.4%
yes 66
 
6.6%
2023-12-09T21:44:28.507901image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 932
45.2%
o 932
45.2%
Y 66
 
3.2%
e 66
 
3.2%
s 66
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1064
51.6%
Uppercase Letter 998
48.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 932
87.6%
e 66
 
6.2%
s 66
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
N 932
93.4%
Y 66
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 2062
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 932
45.2%
o 932
45.2%
Y 66
 
3.2%
e 66
 
3.2%
s 66
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2062
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 932
45.2%
o 932
45.2%
Y 66
 
3.2%
e 66
 
3.2%
s 66
 
3.2%

qwelfare3
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size58.5 KiB
2023-12-09T21:44:28.628071image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.854709419
Min length2

Characters and Unicode

Total characters2849
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 853
85.5%
no 145
 
14.5%
2023-12-09T21:44:28.860938image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 853
29.9%
e 853
29.9%
s 853
29.9%
N 145
 
5.1%
o 145
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1851
65.0%
Uppercase Letter 998
35.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 853
46.1%
s 853
46.1%
o 145
 
7.8%
Uppercase Letter
ValueCountFrequency (%)
Y 853
85.5%
N 145
 
14.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 2849
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 853
29.9%
e 853
29.9%
s 853
29.9%
N 145
 
5.1%
o 145
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2849
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 853
29.9%
e 853
29.9%
s 853
29.9%
N 145
 
5.1%
o 145
 
5.1%

qwelfare4
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:44:28.970267image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.011022044
Min length2

Characters and Unicode

Total characters2007
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 987
98.9%
yes 11
 
1.1%
2023-12-09T21:44:29.195713image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 987
49.2%
o 987
49.2%
Y 11
 
0.5%
e 11
 
0.5%
s 11
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1009
50.3%
Uppercase Letter 998
49.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 987
97.8%
e 11
 
1.1%
s 11
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
N 987
98.9%
Y 11
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 2007
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 987
49.2%
o 987
49.2%
Y 11
 
0.5%
e 11
 
0.5%
s 11
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2007
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 987
49.2%
o 987
49.2%
Y 11
 
0.5%
e 11
 
0.5%
s 11
 
0.5%

qwelfare5
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:44:29.306332image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.001002004
Min length2

Characters and Unicode

Total characters1997
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 997
99.9%
yes 1
 
0.1%
2023-12-09T21:44:29.529585image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 997
49.9%
o 997
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 999
50.0%
Uppercase Letter 998
50.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 997
99.8%
e 1
 
0.1%
s 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 997
99.9%
Y 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 1997
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 997
49.9%
o 997
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1997
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 997
49.9%
o 997
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

qdisability1
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:44:30.571599image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.02004008
Min length2

Characters and Unicode

Total characters2016
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 978
98.0%
yes 20
 
2.0%
2023-12-09T21:44:30.795584image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 978
48.5%
o 978
48.5%
Y 20
 
1.0%
e 20
 
1.0%
s 20
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1018
50.5%
Uppercase Letter 998
49.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 978
96.1%
e 20
 
2.0%
s 20
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
N 978
98.0%
Y 20
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2016
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 978
48.5%
o 978
48.5%
Y 20
 
1.0%
e 20
 
1.0%
s 20
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 978
48.5%
o 978
48.5%
Y 20
 
1.0%
e 20
 
1.0%
s 20
 
1.0%

qdisability2
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:44:30.903853image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.017034068
Min length2

Characters and Unicode

Total characters2013
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 981
98.3%
yes 17
 
1.7%
2023-12-09T21:44:31.141977image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 981
48.7%
o 981
48.7%
Y 17
 
0.8%
e 17
 
0.8%
s 17
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1015
50.4%
Uppercase Letter 998
49.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 981
96.7%
e 17
 
1.7%
s 17
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
N 981
98.3%
Y 17
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 2013
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 981
48.7%
o 981
48.7%
Y 17
 
0.8%
e 17
 
0.8%
s 17
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2013
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 981
48.7%
o 981
48.7%
Y 17
 
0.8%
e 17
 
0.8%
s 17
 
0.8%

qdisability3
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.8 KiB
2023-12-09T21:44:31.255740image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.074148297
Min length2

Characters and Unicode

Total characters2070
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 924
92.6%
yes 74
 
7.4%
2023-12-09T21:44:31.479462image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 924
44.6%
o 924
44.6%
Y 74
 
3.6%
e 74
 
3.6%
s 74
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1072
51.8%
Uppercase Letter 998
48.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 924
86.2%
e 74
 
6.9%
s 74
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
N 924
92.6%
Y 74
 
7.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 2070
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 924
44.6%
o 924
44.6%
Y 74
 
3.6%
e 74
 
3.6%
s 74
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2070
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 924
44.6%
o 924
44.6%
Y 74
 
3.6%
e 74
 
3.6%
s 74
 
3.6%

qdisability4
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:44:31.592031image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.0250501
Min length2

Characters and Unicode

Total characters2021
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 973
97.5%
yes 25
 
2.5%
2023-12-09T21:44:31.814694image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 973
48.1%
o 973
48.1%
Y 25
 
1.2%
e 25
 
1.2%
s 25
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1023
50.6%
Uppercase Letter 998
49.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 973
95.1%
e 25
 
2.4%
s 25
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
N 973
97.5%
Y 25
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 2021
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 973
48.1%
o 973
48.1%
Y 25
 
1.2%
e 25
 
1.2%
s 25
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2021
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 973
48.1%
o 973
48.1%
Y 25
 
1.2%
e 25
 
1.2%
s 25
 
1.2%

qdisability5
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:44:31.924087image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.012024048
Min length2

Characters and Unicode

Total characters2008
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 986
98.8%
yes 12
 
1.2%
2023-12-09T21:44:32.150653image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 986
49.1%
o 986
49.1%
Y 12
 
0.6%
e 12
 
0.6%
s 12
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1010
50.3%
Uppercase Letter 998
49.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 986
97.6%
e 12
 
1.2%
s 12
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
N 986
98.8%
Y 12
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 2008
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 986
49.1%
o 986
49.1%
Y 12
 
0.6%
e 12
 
0.6%
s 12
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 986
49.1%
o 986
49.1%
Y 12
 
0.6%
e 12
 
0.6%
s 12
 
0.6%

qdisability6
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:44:32.267698image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.033066132
Min length2

Characters and Unicode

Total characters2029
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 965
96.7%
yes 33
 
3.3%
2023-12-09T21:44:32.496289image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 965
47.6%
o 965
47.6%
Y 33
 
1.6%
e 33
 
1.6%
s 33
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1031
50.8%
Uppercase Letter 998
49.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 965
93.6%
e 33
 
3.2%
s 33
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
N 965
96.7%
Y 33
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 2029
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 965
47.6%
o 965
47.6%
Y 33
 
1.6%
e 33
 
1.6%
s 33
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2029
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 965
47.6%
o 965
47.6%
Y 33
 
1.6%
e 33
 
1.6%
s 33
 
1.6%

qdisability7
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size58.5 KiB
2023-12-09T21:44:32.616168image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.842685371
Min length2

Characters and Unicode

Total characters2837
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 841
84.3%
no 157
 
15.7%
2023-12-09T21:44:32.848980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 841
29.6%
e 841
29.6%
s 841
29.6%
N 157
 
5.5%
o 157
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1839
64.8%
Uppercase Letter 998
35.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 841
45.7%
s 841
45.7%
o 157
 
8.5%
Uppercase Letter
ValueCountFrequency (%)
Y 841
84.3%
N 157
 
15.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 2837
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 841
29.6%
e 841
29.6%
s 841
29.6%
N 157
 
5.5%
o 157
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2837
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 841
29.6%
e 841
29.6%
s 841
29.6%
N 157
 
5.5%
o 157
 
5.5%

qdisability8
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:44:32.958288image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.011022044
Min length2

Characters and Unicode

Total characters2007
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 987
98.9%
yes 11
 
1.1%
2023-12-09T21:44:33.190500image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 987
49.2%
o 987
49.2%
Y 11
 
0.5%
e 11
 
0.5%
s 11
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1009
50.3%
Uppercase Letter 998
49.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 987
97.8%
e 11
 
1.1%
s 11
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
N 987
98.9%
Y 11
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 2007
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 987
49.2%
o 987
49.2%
Y 11
 
0.5%
e 11
 
0.5%
s 11
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2007
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 987
49.2%
o 987
49.2%
Y 11
 
0.5%
e 11
 
0.5%
s 11
 
0.5%

qdisability9
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:44:33.298393image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1996
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 998
100.0%
2023-12-09T21:44:33.507021image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 998
50.0%
o 998
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 998
50.0%
Lowercase Letter 998
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 998
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 998
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1996
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 998
50.0%
o 998
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1996
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 998
50.0%
o 998
50.0%

qbuildingb
Text

MISSING 

Distinct8
Distinct (%)0.8%
Missing15
Missing (%)1.5%
Memory size93.8 KiB
2023-12-09T21:44:33.715298image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length49
Median length37
Mean length39.86192893
Min length7

Characters and Unicode

Total characters39264
Distinct characters35
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowA building with 2 to 9 apartments
2nd rowA building with 10 to 49 apartments
3rd rowA building with 10 to 49 apartments
4th rowA building with 50 or more apartments
5th rowA building with 50 or more apartments
ValueCountFrequency (%)
a 980
12.7%
apartments 630
 
8.2%
with 630
 
8.2%
building 630
 
8.2%
house 576
 
7.5%
to 495
 
6.4%
one 474
 
6.2%
more 383
 
5.0%
or 383
 
5.0%
family 350
 
4.5%
Other values (20) 2166
28.1%
2023-12-09T21:44:34.050198image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6712
17.1%
t 3088
 
7.9%
e 2999
 
7.6%
o 2890
 
7.4%
a 2315
 
5.9%
i 2241
 
5.7%
n 1961
 
5.0%
h 1908
 
4.9%
r 1850
 
4.7%
m 1593
 
4.1%
Other values (25) 11707
29.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 29854
76.0%
Space Separator 6712
 
17.1%
Decimal Number 1706
 
4.3%
Uppercase Letter 987
 
2.5%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 3088
10.3%
e 2999
 
10.0%
o 2890
 
9.7%
a 2315
 
7.8%
i 2241
 
7.5%
n 1961
 
6.6%
h 1908
 
6.4%
r 1850
 
6.2%
m 1593
 
5.3%
s 1460
 
4.9%
Other values (11) 7549
25.3%
Decimal Number
ValueCountFrequency (%)
0 482
28.3%
9 371
21.7%
5 259
15.2%
4 223
13.1%
1 223
13.1%
2 148
 
8.7%
Uppercase Letter
ValueCountFrequency (%)
A 980
99.3%
R 3
 
0.3%
I 2
 
0.2%
B 1
 
0.1%
V 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
. 1
 
20.0%
Space Separator
ValueCountFrequency (%)
6712
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 30841
78.5%
Common 8423
 
21.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 3088
 
10.0%
e 2999
 
9.7%
o 2890
 
9.4%
a 2315
 
7.5%
i 2241
 
7.3%
n 1961
 
6.4%
h 1908
 
6.2%
r 1850
 
6.0%
m 1593
 
5.2%
s 1460
 
4.7%
Other values (16) 8536
27.7%
Common
ValueCountFrequency (%)
6712
79.7%
0 482
 
5.7%
9 371
 
4.4%
5 259
 
3.1%
4 223
 
2.6%
1 223
 
2.6%
2 148
 
1.8%
, 4
 
< 0.1%
. 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39264
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6712
17.1%
t 3088
 
7.9%
e 2999
 
7.6%
o 2890
 
7.4%
a 2315
 
5.9%
i 2241
 
5.7%
n 1961
 
5.0%
h 1908
 
4.9%
r 1850
 
4.7%
m 1593
 
4.1%
Other values (25) 11707
29.8%

qrent
Text

MISSING 

Distinct3
Distinct (%)0.3%
Missing33
Missing (%)3.3%
Memory size58.3 KiB
2023-12-09T21:44:34.195145image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length4
Mean length3.560496381
Min length3

Characters and Unicode

Total characters3443
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowOwn
2nd rowOwn
3rd rowRent
4th rowOwn
5th rowOwn
ValueCountFrequency (%)
rent 538
55.6%
own 428
44.3%
refused 1
 
0.1%
2023-12-09T21:44:34.460347image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 966
28.1%
e 540
15.7%
R 539
15.7%
t 538
15.6%
O 428
12.4%
w 428
12.4%
f 1
 
< 0.1%
u 1
 
< 0.1%
s 1
 
< 0.1%
d 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2476
71.9%
Uppercase Letter 967
 
28.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 966
39.0%
e 540
21.8%
t 538
21.7%
w 428
17.3%
f 1
 
< 0.1%
u 1
 
< 0.1%
s 1
 
< 0.1%
d 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
R 539
55.7%
O 428
44.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 3443
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 966
28.1%
e 540
15.7%
R 539
15.7%
t 538
15.6%
O 428
12.4%
w 428
12.4%
f 1
 
< 0.1%
u 1
 
< 0.1%
s 1
 
< 0.1%
d 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3443
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 966
28.1%
e 540
15.7%
R 539
15.7%
t 538
15.6%
O 428
12.4%
w 428
12.4%
f 1
 
< 0.1%
u 1
 
< 0.1%
s 1
 
< 0.1%
d 1
 
< 0.1%

qchildren
Text

Distinct5
Distinct (%)0.5%
Missing8
Missing (%)0.8%
Memory size59.3 KiB
2023-12-09T21:44:34.600699image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length4
Mean length3.855846774
Min length3

Characters and Unicode

Total characters3825
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNone
2nd rowNone
3rd rowNone
4th rowNone
5th rowNone
ValueCountFrequency (%)
none 719
71.0%
one 146
 
14.4%
two 97
 
9.6%
three 20
 
2.0%
four 10
 
1.0%
or 10
 
1.0%
more 10
 
1.0%
2023-12-09T21:44:34.857708image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 915
23.9%
n 865
22.6%
o 846
22.1%
N 719
18.8%
O 146
 
3.8%
T 117
 
3.1%
w 97
 
2.5%
r 50
 
1.3%
h 20
 
0.5%
20
 
0.5%
Other values (3) 30
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2813
73.5%
Uppercase Letter 992
 
25.9%
Space Separator 20
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 915
32.5%
n 865
30.8%
o 846
30.1%
w 97
 
3.4%
r 50
 
1.8%
h 20
 
0.7%
u 10
 
0.4%
m 10
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N 719
72.5%
O 146
 
14.7%
T 117
 
11.8%
F 10
 
1.0%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3805
99.5%
Common 20
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 915
24.0%
n 865
22.7%
o 846
22.2%
N 719
18.9%
O 146
 
3.8%
T 117
 
3.1%
w 97
 
2.5%
r 50
 
1.3%
h 20
 
0.5%
F 10
 
0.3%
Other values (2) 20
 
0.5%
Common
ValueCountFrequency (%)
20
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3825
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 915
23.9%
n 865
22.6%
o 846
22.1%
N 719
18.8%
O 146
 
3.8%
T 117
 
3.1%
w 97
 
2.5%
r 50
 
1.3%
h 20
 
0.5%
20
 
0.5%
Other values (3) 30
 
0.8%

gchild1_qchild1_ma
Text

MISSING 

Distinct2
Distinct (%)0.7%
Missing728
Missing (%)72.8%
Memory size38.8 KiB
2023-12-09T21:44:34.978364image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.775735294
Min length2

Characters and Unicode

Total characters755
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowNo
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 211
77.6%
no 61
 
22.4%
2023-12-09T21:44:35.208142image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 211
27.9%
e 211
27.9%
s 211
27.9%
N 61
 
8.1%
o 61
 
8.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 483
64.0%
Uppercase Letter 272
36.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 211
43.7%
s 211
43.7%
o 61
 
12.6%
Uppercase Letter
ValueCountFrequency (%)
Y 211
77.6%
N 61
 
22.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 755
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 211
27.9%
e 211
27.9%
s 211
27.9%
N 61
 
8.1%
o 61
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 755
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 211
27.9%
e 211
27.9%
s 211
27.9%
N 61
 
8.1%
o 61
 
8.1%

gchild1_qchild2_ma
Text

MISSING 

Distinct2
Distinct (%)1.6%
Missing874
Missing (%)87.4%
Memory size34.8 KiB
2023-12-09T21:44:35.329912image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.753968254
Min length2

Characters and Unicode

Total characters347
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowNo
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 95
75.4%
no 31
 
24.6%
2023-12-09T21:44:35.562198image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 95
27.4%
e 95
27.4%
s 95
27.4%
N 31
 
8.9%
o 31
 
8.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 221
63.7%
Uppercase Letter 126
36.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 95
43.0%
s 95
43.0%
o 31
 
14.0%
Uppercase Letter
ValueCountFrequency (%)
Y 95
75.4%
N 31
 
24.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 347
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 95
27.4%
e 95
27.4%
s 95
27.4%
N 31
 
8.9%
o 31
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 347
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 95
27.4%
e 95
27.4%
s 95
27.4%
N 31
 
8.9%
o 31
 
8.9%

gchild1_qchild3_ma
Text

MISSING 

Distinct2
Distinct (%)6.9%
Missing971
Missing (%)97.1%
Memory size32.2 KiB
2023-12-09T21:44:35.683640image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.620689655
Min length2

Characters and Unicode

Total characters76
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowYes
4th rowNo
5th rowYes
ValueCountFrequency (%)
yes 18
62.1%
no 11
37.9%
2023-12-09T21:44:35.933686image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 18
23.7%
e 18
23.7%
s 18
23.7%
N 11
14.5%
o 11
14.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 47
61.8%
Uppercase Letter 29
38.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 18
38.3%
s 18
38.3%
o 11
23.4%
Uppercase Letter
ValueCountFrequency (%)
Y 18
62.1%
N 11
37.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 76
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 18
23.7%
e 18
23.7%
s 18
23.7%
N 11
14.5%
o 11
14.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 18
23.7%
e 18
23.7%
s 18
23.7%
N 11
14.5%
o 11
14.5%

gchild1_qchild4_ma
Text

MISSING 

Distinct2
Distinct (%)22.2%
Missing991
Missing (%)99.1%
Memory size31.6 KiB
2023-12-09T21:44:36.067815image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.555555556
Min length2

Characters and Unicode

Total characters23
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowYes
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
yes 5
55.6%
no 4
44.4%
2023-12-09T21:44:36.322555image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 5
21.7%
e 5
21.7%
s 5
21.7%
N 4
17.4%
o 4
17.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14
60.9%
Uppercase Letter 9
39.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5
35.7%
s 5
35.7%
o 4
28.6%
Uppercase Letter
ValueCountFrequency (%)
Y 5
55.6%
N 4
44.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 23
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 5
21.7%
e 5
21.7%
s 5
21.7%
N 4
17.4%
o 4
17.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 5
21.7%
e 5
21.7%
s 5
21.7%
N 4
17.4%
o 4
17.4%

qchild1schooladdr
Text

MISSING 

Distinct6
Distinct (%)2.8%
Missing789
Missing (%)78.9%
Memory size38.4 KiB
2023-12-09T21:44:36.520379image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length14
Median length13
Mean length8.976303318
Min length6

Characters and Unicode

Total characters1894
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowManhattan
2nd rowThe Bronx
3rd rowManhattan
4th rowStaten Island
5th rowStaten Island
ValueCountFrequency (%)
the 48
15.8%
bronx 48
15.8%
manhattan 44
14.5%
queens 41
13.5%
brooklyn 40
13.2%
staten 32
10.6%
island 32
10.6%
outside 6
 
2.0%
of 6
 
2.0%
nyc 6
 
2.0%
2023-12-09T21:44:36.851216image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 281
14.8%
a 196
 
10.3%
e 168
 
8.9%
t 158
 
8.3%
o 134
 
7.1%
h 92
 
4.9%
92
 
4.9%
B 88
 
4.6%
r 88
 
4.6%
s 79
 
4.2%
Other values (17) 518
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1493
78.8%
Uppercase Letter 309
 
16.3%
Space Separator 92
 
4.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 281
18.8%
a 196
13.1%
e 168
11.3%
t 158
10.6%
o 134
9.0%
h 92
 
6.2%
r 88
 
5.9%
s 79
 
5.3%
l 72
 
4.8%
x 48
 
3.2%
Other values (6) 177
11.9%
Uppercase Letter
ValueCountFrequency (%)
B 88
28.5%
T 48
15.5%
M 44
14.2%
Q 41
13.3%
S 32
 
10.4%
I 32
 
10.4%
O 6
 
1.9%
N 6
 
1.9%
Y 6
 
1.9%
C 6
 
1.9%
Space Separator
ValueCountFrequency (%)
92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1802
95.1%
Common 92
 
4.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 281
15.6%
a 196
10.9%
e 168
 
9.3%
t 158
 
8.8%
o 134
 
7.4%
h 92
 
5.1%
B 88
 
4.9%
r 88
 
4.9%
s 79
 
4.4%
l 72
 
4.0%
Other values (16) 446
24.8%
Common
ValueCountFrequency (%)
92
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1894
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 281
14.8%
a 196
 
10.3%
e 168
 
8.9%
t 158
 
8.3%
o 134
 
7.1%
h 92
 
4.9%
92
 
4.9%
B 88
 
4.6%
r 88
 
4.6%
s 79
 
4.2%
Other values (17) 518
27.3%

qchild2schooladdr
Text

MISSING 

Distinct5
Distinct (%)5.3%
Missing905
Missing (%)90.5%
Memory size34.5 KiB
2023-12-09T21:44:37.034373image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length13
Median length9
Mean length8.884210526
Min length6

Characters and Unicode

Total characters844
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowManhattan
2nd rowStaten Island
3rd rowStaten Island
4th rowBrooklyn
5th rowThe Bronx
ValueCountFrequency (%)
brooklyn 25
19.5%
manhattan 23
18.0%
the 19
14.8%
bronx 19
14.8%
staten 14
10.9%
island 14
10.9%
queens 14
10.9%
2023-12-09T21:44:37.352168image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 132
15.6%
a 97
11.5%
t 74
 
8.8%
o 69
 
8.2%
e 61
 
7.2%
r 44
 
5.2%
B 44
 
5.2%
h 42
 
5.0%
l 39
 
4.6%
33
 
3.9%
Other values (11) 209
24.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 683
80.9%
Uppercase Letter 128
 
15.2%
Space Separator 33
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 132
19.3%
a 97
14.2%
t 74
10.8%
o 69
10.1%
e 61
8.9%
r 44
 
6.4%
h 42
 
6.1%
l 39
 
5.7%
s 28
 
4.1%
y 25
 
3.7%
Other values (4) 72
10.5%
Uppercase Letter
ValueCountFrequency (%)
B 44
34.4%
M 23
18.0%
T 19
14.8%
S 14
 
10.9%
I 14
 
10.9%
Q 14
 
10.9%
Space Separator
ValueCountFrequency (%)
33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 811
96.1%
Common 33
 
3.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 132
16.3%
a 97
12.0%
t 74
9.1%
o 69
 
8.5%
e 61
 
7.5%
r 44
 
5.4%
B 44
 
5.4%
h 42
 
5.2%
l 39
 
4.8%
s 28
 
3.5%
Other values (10) 181
22.3%
Common
ValueCountFrequency (%)
33
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 844
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 132
15.6%
a 97
11.5%
t 74
 
8.8%
o 69
 
8.2%
e 61
 
7.2%
r 44
 
5.2%
B 44
 
5.2%
h 42
 
5.0%
l 39
 
4.6%
33
 
3.9%
Other values (11) 209
24.8%

qchild3schooladdr
Text

MISSING 

Distinct5
Distinct (%)27.8%
Missing982
Missing (%)98.2%
Memory size32.0 KiB
2023-12-09T21:44:37.527672image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length14
Median length9
Mean length8.777777778
Min length6

Characters and Unicode

Total characters158
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)11.1%

Sample

1st rowOutside of NYC
2nd rowBrooklyn
3rd rowManhattan
4th rowBrooklyn
5th rowThe Bronx
ValueCountFrequency (%)
brooklyn 6
25.0%
manhattan 6
25.0%
the 4
16.7%
bronx 4
16.7%
outside 1
 
4.2%
of 1
 
4.2%
nyc 1
 
4.2%
queens 1
 
4.2%
2023-12-09T21:44:37.838562image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 23
14.6%
a 18
11.4%
o 17
10.8%
t 13
 
8.2%
B 10
 
6.3%
r 10
 
6.3%
h 10
 
6.3%
e 7
 
4.4%
M 6
 
3.8%
y 6
 
3.8%
Other values (15) 38
24.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 127
80.4%
Uppercase Letter 25
 
15.8%
Space Separator 6
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 23
18.1%
a 18
14.2%
o 17
13.4%
t 13
10.2%
r 10
7.9%
h 10
7.9%
e 7
 
5.5%
y 6
 
4.7%
l 6
 
4.7%
k 6
 
4.7%
Other values (6) 11
8.7%
Uppercase Letter
ValueCountFrequency (%)
B 10
40.0%
M 6
24.0%
T 4
 
16.0%
O 1
 
4.0%
N 1
 
4.0%
Y 1
 
4.0%
C 1
 
4.0%
Q 1
 
4.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 152
96.2%
Common 6
 
3.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 23
15.1%
a 18
11.8%
o 17
11.2%
t 13
8.6%
B 10
 
6.6%
r 10
 
6.6%
h 10
 
6.6%
e 7
 
4.6%
M 6
 
3.9%
y 6
 
3.9%
Other values (14) 32
21.1%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 158
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 23
14.6%
a 18
11.4%
o 17
10.8%
t 13
 
8.2%
B 10
 
6.3%
r 10
 
6.3%
h 10
 
6.3%
e 7
 
4.4%
M 6
 
3.8%
y 6
 
3.8%
Other values (15) 38
24.1%

qchild4schooladdr
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing996
Missing (%)99.6%
Memory size31.5 KiB
2023-12-09T21:44:37.948783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st row4
2nd row2
3rd row2
4th row2
ValueCountFrequency (%)
2 3
75.0%
4 1
 
25.0%
2023-12-09T21:44:38.158162image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3
75.0%
4 1
 
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3
75.0%
4 1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3
75.0%
4 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3
75.0%
4 1
 
25.0%

qaccompany
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size37.1 KiB
2023-12-09T21:44:38.282369image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.630331754
Min length2

Characters and Unicode

Total characters555
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowYes
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
yes 133
63.0%
no 78
37.0%
2023-12-09T21:44:38.526635image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 133
24.0%
e 133
24.0%
s 133
24.0%
N 78
14.1%
o 78
14.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 344
62.0%
Uppercase Letter 211
38.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 133
38.7%
s 133
38.7%
o 78
22.7%
Uppercase Letter
ValueCountFrequency (%)
Y 133
63.0%
N 78
37.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 555
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 133
24.0%
e 133
24.0%
s 133
24.0%
N 78
14.1%
o 78
14.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 555
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 133
24.0%
e 133
24.0%
s 133
24.0%
N 78
14.1%
o 78
14.1%

qschooltravelcode01
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size37.0 KiB
2023-12-09T21:44:38.658912image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.412322275
Min length2

Characters and Unicode

Total characters509
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowNo
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 124
58.8%
yes 87
41.2%
2023-12-09T21:44:38.907663image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 124
24.4%
o 124
24.4%
Y 87
17.1%
e 87
17.1%
s 87
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 298
58.5%
Uppercase Letter 211
41.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 124
41.6%
e 87
29.2%
s 87
29.2%
Uppercase Letter
ValueCountFrequency (%)
N 124
58.8%
Y 87
41.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 509
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 124
24.4%
o 124
24.4%
Y 87
17.1%
e 87
17.1%
s 87
17.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 509
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 124
24.4%
o 124
24.4%
Y 87
17.1%
e 87
17.1%
s 87
17.1%

qschooltravelcode02
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size37.0 KiB
2023-12-09T21:44:39.040623image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.412322275
Min length2

Characters and Unicode

Total characters509
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 124
58.8%
yes 87
41.2%
2023-12-09T21:44:39.294187image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 124
24.4%
o 124
24.4%
Y 87
17.1%
e 87
17.1%
s 87
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 298
58.5%
Uppercase Letter 211
41.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 124
41.6%
e 87
29.2%
s 87
29.2%
Uppercase Letter
ValueCountFrequency (%)
N 124
58.8%
Y 87
41.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 509
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 124
24.4%
o 124
24.4%
Y 87
17.1%
e 87
17.1%
s 87
17.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 509
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 124
24.4%
o 124
24.4%
Y 87
17.1%
e 87
17.1%
s 87
17.1%

qschooltravelcode03
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size37.0 KiB
2023-12-09T21:44:39.407262image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.075829384
Min length2

Characters and Unicode

Total characters438
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 195
92.4%
yes 16
 
7.6%
2023-12-09T21:44:39.629827image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 195
44.5%
o 195
44.5%
Y 16
 
3.7%
e 16
 
3.7%
s 16
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 227
51.8%
Uppercase Letter 211
48.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 195
85.9%
e 16
 
7.0%
s 16
 
7.0%
Uppercase Letter
ValueCountFrequency (%)
N 195
92.4%
Y 16
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 438
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 195
44.5%
o 195
44.5%
Y 16
 
3.7%
e 16
 
3.7%
s 16
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 438
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 195
44.5%
o 195
44.5%
Y 16
 
3.7%
e 16
 
3.7%
s 16
 
3.7%

qschooltravelcode04
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size37.0 KiB
2023-12-09T21:44:39.742875image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.123222749
Min length2

Characters and Unicode

Total characters448
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 185
87.7%
yes 26
 
12.3%
2023-12-09T21:44:39.975157image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 185
41.3%
o 185
41.3%
Y 26
 
5.8%
e 26
 
5.8%
s 26
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 237
52.9%
Uppercase Letter 211
47.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 185
78.1%
e 26
 
11.0%
s 26
 
11.0%
Uppercase Letter
ValueCountFrequency (%)
N 185
87.7%
Y 26
 
12.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 448
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 185
41.3%
o 185
41.3%
Y 26
 
5.8%
e 26
 
5.8%
s 26
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 448
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 185
41.3%
o 185
41.3%
Y 26
 
5.8%
e 26
 
5.8%
s 26
 
5.8%

qschooltravelcode05
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:40.083060image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.014218009
Min length2

Characters and Unicode

Total characters425
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 208
98.6%
yes 3
 
1.4%
2023-12-09T21:44:40.317828image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 208
48.9%
o 208
48.9%
Y 3
 
0.7%
e 3
 
0.7%
s 3
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 214
50.4%
Uppercase Letter 211
49.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 208
97.2%
e 3
 
1.4%
s 3
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
N 208
98.6%
Y 3
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 425
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 208
48.9%
o 208
48.9%
Y 3
 
0.7%
e 3
 
0.7%
s 3
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 425
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 208
48.9%
o 208
48.9%
Y 3
 
0.7%
e 3
 
0.7%
s 3
 
0.7%

qschooltravelcode06
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:40.426532image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.004739336
Min length2

Characters and Unicode

Total characters423
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 210
99.5%
yes 1
 
0.5%
2023-12-09T21:44:40.650461image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 212
50.1%
Uppercase Letter 211
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 210
99.1%
e 1
 
0.5%
s 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 210
99.5%
Y 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 423
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

qschooltravelcode07
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:40.752876image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters422
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 211
100.0%
2023-12-09T21:44:40.957324image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 211
50.0%
Lowercase Letter 211
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 211
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 422
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

qschooltravelcode08
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:41.058215image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters422
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 211
100.0%
2023-12-09T21:44:41.275611image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 211
50.0%
Lowercase Letter 211
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 211
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 422
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

qschooltravelcode09
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:41.379012image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters422
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 211
100.0%
2023-12-09T21:44:41.594281image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 211
50.0%
Lowercase Letter 211
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 211
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 422
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

qschooltravelcode10
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:41.703083image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.004739336
Min length2

Characters and Unicode

Total characters423
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 210
99.5%
yes 1
 
0.5%
2023-12-09T21:44:41.924630image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 212
50.1%
Uppercase Letter 211
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 210
99.1%
e 1
 
0.5%
s 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 210
99.5%
Y 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 423
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

qschooltravelcode11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:42.026206image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters422
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 211
100.0%
2023-12-09T21:44:42.233335image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 211
50.0%
Lowercase Letter 211
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 211
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 422
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

qschooltravelcode12
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size37.0 KiB
2023-12-09T21:44:42.356493image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.274881517
Min length2

Characters and Unicode

Total characters480
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 153
72.5%
yes 58
 
27.5%
2023-12-09T21:44:42.593646image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 153
31.9%
o 153
31.9%
Y 58
 
12.1%
e 58
 
12.1%
s 58
 
12.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 269
56.0%
Uppercase Letter 211
44.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 153
56.9%
e 58
 
21.6%
s 58
 
21.6%
Uppercase Letter
ValueCountFrequency (%)
N 153
72.5%
Y 58
 
27.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 480
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 153
31.9%
o 153
31.9%
Y 58
 
12.1%
e 58
 
12.1%
s 58
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 480
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 153
31.9%
o 153
31.9%
Y 58
 
12.1%
e 58
 
12.1%
s 58
 
12.1%

qschooltravelcode13
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:42.704131image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.004739336
Min length2

Characters and Unicode

Total characters423
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 210
99.5%
yes 1
 
0.5%
2023-12-09T21:44:42.930140image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 212
50.1%
Uppercase Letter 211
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 210
99.1%
e 1
 
0.5%
s 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 210
99.5%
Y 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 423
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

qschooltravelcode14
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:43.039541image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.014218009
Min length2

Characters and Unicode

Total characters425
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 208
98.6%
yes 3
 
1.4%
2023-12-09T21:44:43.264923image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 208
48.9%
o 208
48.9%
Y 3
 
0.7%
e 3
 
0.7%
s 3
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 214
50.4%
Uppercase Letter 211
49.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 208
97.2%
e 3
 
1.4%
s 3
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
N 208
98.6%
Y 3
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 425
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 208
48.9%
o 208
48.9%
Y 3
 
0.7%
e 3
 
0.7%
s 3
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 425
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 208
48.9%
o 208
48.9%
Y 3
 
0.7%
e 3
 
0.7%
s 3
 
0.7%

qschooltravelcode15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:43.368847image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters422
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 211
100.0%
2023-12-09T21:44:43.580972image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 211
50.0%
Lowercase Letter 211
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 211
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 422
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

qschooltravelcode16
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:43.688190image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters422
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 211
100.0%
2023-12-09T21:44:43.895797image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 211
50.0%
Lowercase Letter 211
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 211
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 422
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

qschooltravelcode17
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:43.996227image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters422
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 211
100.0%
2023-12-09T21:44:44.201313image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 211
50.0%
Lowercase Letter 211
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 211
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 422
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

qschooltravelcode18
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:44.306237image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters422
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 211
100.0%
2023-12-09T21:44:44.512362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 211
50.0%
Lowercase Letter 211
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 211
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 422
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

qschooltravelcode19
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:44.618534image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.004739336
Min length2

Characters and Unicode

Total characters423
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 210
99.5%
yes 1
 
0.5%
2023-12-09T21:44:44.839890image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 212
50.1%
Uppercase Letter 211
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 210
99.1%
e 1
 
0.5%
s 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 210
99.5%
Y 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 423
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

qschooltravelcode20
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:44.946699image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.004739336
Min length2

Characters and Unicode

Total characters423
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 210
99.5%
yes 1
 
0.5%
2023-12-09T21:44:45.168084image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 212
50.1%
Uppercase Letter 211
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 210
99.1%
e 1
 
0.5%
s 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 210
99.5%
Y 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 423
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

qschooltravelcode21
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:45.269356image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters422
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 211
100.0%
2023-12-09T21:44:45.484393image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 211
50.0%
Lowercase Letter 211
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 211
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 422
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

qschooltravelcode22
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:45.590447image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.004739336
Min length2

Characters and Unicode

Total characters423
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 210
99.5%
yes 1
 
0.5%
2023-12-09T21:44:45.813700image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 212
50.1%
Uppercase Letter 211
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 210
99.1%
e 1
 
0.5%
s 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 210
99.5%
Y 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 423
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

qschooltravelcode23
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:45.919200image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters422
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 211
100.0%
2023-12-09T21:44:46.131787image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 211
50.0%
Lowercase Letter 211
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 211
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 422
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

qschooltravelcode24
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:46.234452image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters422
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 211
100.0%
2023-12-09T21:44:46.451211image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 211
50.0%
Lowercase Letter 211
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 211
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 422
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

qschooltravelcode25
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:46.566229image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.004739336
Min length2

Characters and Unicode

Total characters423
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 210
99.5%
yes 1
 
0.5%
2023-12-09T21:44:46.795265image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 212
50.1%
Uppercase Letter 211
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 210
99.1%
e 1
 
0.5%
s 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 210
99.5%
Y 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 423
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

qschooltravelcode26
Text

MISSING 

Distinct2
Distinct (%)0.9%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:46.904657image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.004739336
Min length2

Characters and Unicode

Total characters423
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 210
99.5%
yes 1
 
0.5%
2023-12-09T21:44:47.127564image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 212
50.1%
Uppercase Letter 211
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 210
99.1%
e 1
 
0.5%
s 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 210
99.5%
Y 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 423
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 423
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 210
49.6%
o 210
49.6%
Y 1
 
0.2%
e 1
 
0.2%
s 1
 
0.2%

qschooltravelcode27
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing789
Missing (%)78.9%
Memory size36.9 KiB
2023-12-09T21:44:47.228709image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters422
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 211
100.0%
2023-12-09T21:44:47.436631image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 211
50.0%
Lowercase Letter 211
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 211
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 422
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 211
50.0%
o 211
50.0%

qschooltransitto1
Text

MISSING 

Distinct2
Distinct (%)4.9%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:47.552853image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.902439024
Min length2

Characters and Unicode

Total characters119
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 37
90.2%
no 4
 
9.8%
2023-12-09T21:44:47.788869image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 37
31.1%
e 37
31.1%
s 37
31.1%
N 4
 
3.4%
o 4
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 78
65.5%
Uppercase Letter 41
34.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 37
47.4%
s 37
47.4%
o 4
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
Y 37
90.2%
N 4
 
9.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 119
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 37
31.1%
e 37
31.1%
s 37
31.1%
N 4
 
3.4%
o 4
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 119
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 37
31.1%
e 37
31.1%
s 37
31.1%
N 4
 
3.4%
o 4
 
3.4%

qschooltransitto2
Text

MISSING 

Distinct2
Distinct (%)4.9%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:47.896021image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.024390244
Min length2

Characters and Unicode

Total characters83
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 40
97.6%
yes 1
 
2.4%
2023-12-09T21:44:48.115906image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 40
48.2%
o 40
48.2%
Y 1
 
1.2%
e 1
 
1.2%
s 1
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 42
50.6%
Uppercase Letter 41
49.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 40
95.2%
e 1
 
2.4%
s 1
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
N 40
97.6%
Y 1
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 83
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 40
48.2%
o 40
48.2%
Y 1
 
1.2%
e 1
 
1.2%
s 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 40
48.2%
o 40
48.2%
Y 1
 
1.2%
e 1
 
1.2%
s 1
 
1.2%

qschooltransitto3
Text

MISSING 

Distinct2
Distinct (%)4.9%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:48.227309image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.048780488
Min length2

Characters and Unicode

Total characters84
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 39
95.1%
yes 2
 
4.9%
2023-12-09T21:44:48.459169image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 39
46.4%
o 39
46.4%
Y 2
 
2.4%
e 2
 
2.4%
s 2
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 43
51.2%
Uppercase Letter 41
48.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 39
90.7%
e 2
 
4.7%
s 2
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
N 39
95.1%
Y 2
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 84
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 39
46.4%
o 39
46.4%
Y 2
 
2.4%
e 2
 
2.4%
s 2
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 39
46.4%
o 39
46.4%
Y 2
 
2.4%
e 2
 
2.4%
s 2
 
2.4%

qschooltransitto4
Text

MISSING 

Distinct2
Distinct (%)4.9%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:48.569795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.024390244
Min length2

Characters and Unicode

Total characters83
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 40
97.6%
yes 1
 
2.4%
2023-12-09T21:44:48.785391image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 40
48.2%
o 40
48.2%
Y 1
 
1.2%
e 1
 
1.2%
s 1
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 42
50.6%
Uppercase Letter 41
49.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 40
95.2%
e 1
 
2.4%
s 1
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
N 40
97.6%
Y 1
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 83
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 40
48.2%
o 40
48.2%
Y 1
 
1.2%
e 1
 
1.2%
s 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 40
48.2%
o 40
48.2%
Y 1
 
1.2%
e 1
 
1.2%
s 1
 
1.2%

qschooltransitto5
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)2.4%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:48.885387image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters82
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 41
100.0%
2023-12-09T21:44:49.091818image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 41
50.0%
Lowercase Letter 41
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 41
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 82
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

qschooltransitto6
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)2.4%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:49.193121image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters82
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 41
100.0%
2023-12-09T21:44:49.399965image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 41
50.0%
Lowercase Letter 41
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 41
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 82
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

qschooltransitto7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)2.4%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:49.499621image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters82
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 41
100.0%
2023-12-09T21:44:50.834288image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 41
50.0%
Lowercase Letter 41
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 41
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 82
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

qschooltransitfrom1
Text

MISSING 

Distinct2
Distinct (%)4.9%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:50.952464image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.926829268
Min length2

Characters and Unicode

Total characters120
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
yes 38
92.7%
no 3
 
7.3%
2023-12-09T21:44:51.187900image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 38
31.7%
e 38
31.7%
s 38
31.7%
N 3
 
2.5%
o 3
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 79
65.8%
Uppercase Letter 41
34.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 38
48.1%
s 38
48.1%
o 3
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
Y 38
92.7%
N 3
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 120
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 38
31.7%
e 38
31.7%
s 38
31.7%
N 3
 
2.5%
o 3
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 38
31.7%
e 38
31.7%
s 38
31.7%
N 3
 
2.5%
o 3
 
2.5%

qschooltransitfrom2
Text

MISSING 

Distinct2
Distinct (%)4.9%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:51.297894image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.048780488
Min length2

Characters and Unicode

Total characters84
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 39
95.1%
yes 2
 
4.9%
2023-12-09T21:44:51.519247image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 39
46.4%
o 39
46.4%
Y 2
 
2.4%
e 2
 
2.4%
s 2
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 43
51.2%
Uppercase Letter 41
48.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 39
90.7%
e 2
 
4.7%
s 2
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
N 39
95.1%
Y 2
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 84
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 39
46.4%
o 39
46.4%
Y 2
 
2.4%
e 2
 
2.4%
s 2
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 39
46.4%
o 39
46.4%
Y 2
 
2.4%
e 2
 
2.4%
s 2
 
2.4%

qschooltransitfrom3
Text

MISSING 

Distinct2
Distinct (%)4.9%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:51.632573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.024390244
Min length2

Characters and Unicode

Total characters83
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 40
97.6%
yes 1
 
2.4%
2023-12-09T21:44:51.849401image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 40
48.2%
o 40
48.2%
Y 1
 
1.2%
e 1
 
1.2%
s 1
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 42
50.6%
Uppercase Letter 41
49.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 40
95.2%
e 1
 
2.4%
s 1
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
N 40
97.6%
Y 1
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 83
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 40
48.2%
o 40
48.2%
Y 1
 
1.2%
e 1
 
1.2%
s 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 40
48.2%
o 40
48.2%
Y 1
 
1.2%
e 1
 
1.2%
s 1
 
1.2%

qschooltransitfrom4
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)2.4%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:51.951443image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters82
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 41
100.0%
2023-12-09T21:44:52.155637image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 41
50.0%
Lowercase Letter 41
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 41
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 82
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

qschooltransitfrom5
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)2.4%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:52.256984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters82
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 41
100.0%
2023-12-09T21:44:52.464215image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 41
50.0%
Lowercase Letter 41
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 41
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 82
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

qschooltransitfrom6
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)2.4%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:52.565013image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters82
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 41
100.0%
2023-12-09T21:44:52.771773image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 41
50.0%
Lowercase Letter 41
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 41
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 82
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

qschooltransitfrom7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)2.4%
Missing959
Missing (%)95.9%
Memory size32.5 KiB
2023-12-09T21:44:52.872063image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters82
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 41
100.0%
2023-12-09T21:44:53.075756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 41
50.0%
Lowercase Letter 41
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 41
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 82
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 41
50.0%
o 41
50.0%

qemployment
Text

Distinct10
Distinct (%)1.0%
Missing9
Missing (%)0.9%
Memory size92.6 KiB
2023-12-09T21:44:53.289202image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length56
Median length56
Mean length38.28657921
Min length5

Characters and Unicode

Total characters37942
Distinct characters35
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowEmployed full time (working more than 30 hours per week)
2nd rowUnemployed
3rd rowRetired
4th rowRetired
5th rowEmployed full time (working more than 30 hours per week)
ValueCountFrequency (%)
time 645
9.8%
employed 603
9.1%
working 603
9.1%
than 603
9.1%
30 603
9.1%
hours 603
9.1%
per 603
9.1%
week 603
9.1%
full 529
8.0%
more 487
7.4%
Other values (16) 710
10.8%
2023-12-09T21:44:53.627900image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5601
14.8%
e 4386
 
11.6%
r 2681
 
7.1%
o 2440
 
6.4%
l 1874
 
4.9%
m 1873
 
4.9%
t 1842
 
4.9%
p 1452
 
3.8%
i 1427
 
3.8%
n 1393
 
3.7%
Other values (25) 12973
34.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 28808
75.9%
Space Separator 5601
 
14.8%
Decimal Number 1213
 
3.2%
Uppercase Letter 991
 
2.6%
Open Punctuation 610
 
1.6%
Close Punctuation 610
 
1.6%
Dash Punctuation 102
 
0.3%
Other Punctuation 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4386
15.2%
r 2681
 
9.3%
o 2440
 
8.5%
l 1874
 
6.5%
m 1873
 
6.5%
t 1842
 
6.4%
p 1452
 
5.0%
i 1427
 
5.0%
n 1393
 
4.8%
h 1282
 
4.5%
Other values (9) 8158
28.3%
Uppercase Letter
ValueCountFrequency (%)
E 603
60.8%
R 172
 
17.4%
U 83
 
8.4%
S 47
 
4.7%
F 42
 
4.2%
O 29
 
2.9%
P 8
 
0.8%
V 7
 
0.7%
Decimal Number
ValueCountFrequency (%)
0 603
49.7%
3 603
49.7%
1 7
 
0.6%
Space Separator
ValueCountFrequency (%)
5601
100.0%
Open Punctuation
ValueCountFrequency (%)
( 610
100.0%
Close Punctuation
ValueCountFrequency (%)
) 610
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 102
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 29799
78.5%
Common 8143
 
21.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4386
14.7%
r 2681
 
9.0%
o 2440
 
8.2%
l 1874
 
6.3%
m 1873
 
6.3%
t 1842
 
6.2%
p 1452
 
4.9%
i 1427
 
4.8%
n 1393
 
4.7%
h 1282
 
4.3%
Other values (17) 9149
30.7%
Common
ValueCountFrequency (%)
5601
68.8%
( 610
 
7.5%
) 610
 
7.5%
0 603
 
7.4%
3 603
 
7.4%
- 102
 
1.3%
1 7
 
0.1%
/ 7
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37942
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5601
14.8%
e 4386
 
11.6%
r 2681
 
7.1%
o 2440
 
6.4%
l 1874
 
4.9%
m 1873
 
4.9%
t 1842
 
4.9%
p 1452
 
3.8%
i 1427
 
3.8%
n 1393
 
3.7%
Other values (25) 12973
34.2%

qemploymentcode
Text

Distinct4
Distinct (%)0.4%
Missing2
Missing (%)0.2%
Memory size66.3 KiB
2023-12-09T21:44:53.797007image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length8
Mean length10.81062124
Min length5

Characters and Unicode

Total characters10789
Distinct characters22
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEmployed
2nd rowUnemployed
3rd rowNot in Labor Force
4th rowNot in Labor Force
5th rowEmployed
ValueCountFrequency (%)
employed 603
33.1%
not 275
15.1%
in 275
15.1%
labor 275
15.1%
force 275
15.1%
unemployed 83
 
4.6%
other 37
 
2.0%
2023-12-09T21:44:54.084813image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1511
14.0%
e 1081
 
10.0%
825
 
7.6%
p 686
 
6.4%
l 686
 
6.4%
y 686
 
6.4%
d 686
 
6.4%
m 686
 
6.4%
E 603
 
5.6%
r 587
 
5.4%
Other values (12) 2752
25.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8416
78.0%
Uppercase Letter 1548
 
14.3%
Space Separator 825
 
7.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1511
18.0%
e 1081
12.8%
p 686
8.2%
l 686
8.2%
y 686
8.2%
d 686
8.2%
m 686
8.2%
r 587
 
7.0%
n 358
 
4.3%
t 312
 
3.7%
Other values (5) 1137
13.5%
Uppercase Letter
ValueCountFrequency (%)
E 603
39.0%
F 275
17.8%
L 275
17.8%
N 275
17.8%
U 83
 
5.4%
O 37
 
2.4%
Space Separator
ValueCountFrequency (%)
825
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9964
92.4%
Common 825
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1511
15.2%
e 1081
10.8%
p 686
 
6.9%
l 686
 
6.9%
y 686
 
6.9%
d 686
 
6.9%
m 686
 
6.9%
E 603
 
6.1%
r 587
 
5.9%
n 358
 
3.6%
Other values (11) 2394
24.0%
Common
ValueCountFrequency (%)
825
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10789
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1511
14.0%
e 1081
 
10.0%
825
 
7.6%
p 686
 
6.4%
l 686
 
6.4%
y 686
 
6.4%
d 686
 
6.4%
m 686
 
6.4%
E 603
 
5.6%
r 587
 
5.4%
Other values (12) 2752
25.5%

qindustry
Text

MISSING 

Distinct18
Distinct (%)3.0%
Missing406
Missing (%)40.6%
Memory size56.8 KiB
2023-12-09T21:44:54.322048image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length63
Median length29
Mean length18.82996633
Min length5

Characters and Unicode

Total characters11185
Distinct characters42
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowNon-profit
2nd rowEducation
3rd rowRetail
4th rowArts & Entertainment
5th rowFinancial services
ValueCountFrequency (%)
126
 
9.7%
services 125
 
9.6%
other 86
 
6.6%
education 82
 
6.3%
financial 68
 
5.2%
consulting 57
 
4.4%
marketing 57
 
4.4%
legal 57
 
4.4%
business 57
 
4.4%
professional 57
 
4.4%
Other values (26) 524
40.4%
2023-12-09T21:44:54.695943image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1068
 
9.5%
i 966
 
8.6%
n 922
 
8.2%
s 841
 
7.5%
a 837
 
7.5%
t 806
 
7.2%
702
 
6.3%
o 597
 
5.3%
c 576
 
5.1%
r 559
 
5.0%
Other values (32) 3311
29.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9083
81.2%
Uppercase Letter 948
 
8.5%
Space Separator 702
 
6.3%
Other Punctuation 300
 
2.7%
Open Punctuation 60
 
0.5%
Close Punctuation 60
 
0.5%
Dash Punctuation 32
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1068
11.8%
i 966
10.6%
n 922
10.2%
s 841
9.3%
a 837
9.2%
t 806
8.9%
o 597
6.6%
c 576
6.3%
r 559
6.2%
l 554
6.1%
Other values (10) 1357
14.9%
Uppercase Letter
ValueCountFrequency (%)
E 117
12.3%
S 111
11.7%
A 89
9.4%
O 86
9.1%
C 78
8.2%
T 71
7.5%
F 68
7.2%
H 67
7.1%
R 58
 
6.1%
B 57
 
6.0%
Other values (5) 146
15.4%
Other Punctuation
ValueCountFrequency (%)
& 126
42.0%
, 120
40.0%
/ 54
18.0%
Space Separator
ValueCountFrequency (%)
702
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10031
89.7%
Common 1154
 
10.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1068
10.6%
i 966
9.6%
n 922
 
9.2%
s 841
 
8.4%
a 837
 
8.3%
t 806
 
8.0%
o 597
 
6.0%
c 576
 
5.7%
r 559
 
5.6%
l 554
 
5.5%
Other values (25) 2305
23.0%
Common
ValueCountFrequency (%)
702
60.8%
& 126
 
10.9%
, 120
 
10.4%
( 60
 
5.2%
) 60
 
5.2%
/ 54
 
4.7%
- 32
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11185
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1068
 
9.5%
i 966
 
8.6%
n 922
 
8.2%
s 841
 
7.5%
a 837
 
7.5%
t 806
 
7.2%
702
 
6.3%
o 597
 
5.3%
c 576
 
5.1%
r 559
 
5.0%
Other values (32) 3311
29.6%

gfulltime_qfulltime_ma
Text

MISSING 

Distinct4
Distinct (%)0.8%
Missing513
Missing (%)51.3%
Memory size43.8 KiB
2023-12-09T21:44:54.821027image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.131416838
Min length1

Characters and Unicode

Total characters551
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 457
90.9%
2 15
 
3.0%
3 8
 
1.6%
or 8
 
1.6%
more 8
 
1.6%
0 7
 
1.4%
2023-12-09T21:44:55.066935image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 457
82.9%
16
 
2.9%
o 16
 
2.9%
r 16
 
2.9%
2 15
 
2.7%
3 8
 
1.5%
m 8
 
1.5%
e 8
 
1.5%
0 7
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 487
88.4%
Lowercase Letter 48
 
8.7%
Space Separator 16
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 457
93.8%
2 15
 
3.1%
3 8
 
1.6%
0 7
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
o 16
33.3%
r 16
33.3%
m 8
16.7%
e 8
16.7%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 503
91.3%
Latin 48
 
8.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 457
90.9%
16
 
3.2%
2 15
 
3.0%
3 8
 
1.6%
0 7
 
1.4%
Latin
ValueCountFrequency (%)
o 16
33.3%
r 16
33.3%
m 8
16.7%
e 8
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 457
82.9%
16
 
2.9%
o 16
 
2.9%
r 16
 
2.9%
2 15
 
2.7%
3 8
 
1.5%
m 8
 
1.5%
e 8
 
1.5%
0 7
 
1.3%

gfulltime_qparttime_ma
Text

MISSING 

Distinct4
Distinct (%)0.7%
Missing400
Missing (%)40.0%
Memory size46.7 KiB
2023-12-09T21:44:55.179873image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.133333333
Min length1

Characters and Unicode

Total characters680
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row1
ValueCountFrequency (%)
0 416
67.1%
1 145
 
23.4%
2 29
 
4.7%
3 10
 
1.6%
or 10
 
1.6%
more 10
 
1.6%
2023-12-09T21:44:55.424304image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 416
61.2%
1 145
 
21.3%
2 29
 
4.3%
20
 
2.9%
o 20
 
2.9%
r 20
 
2.9%
3 10
 
1.5%
m 10
 
1.5%
e 10
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 600
88.2%
Lowercase Letter 60
 
8.8%
Space Separator 20
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 416
69.3%
1 145
 
24.2%
2 29
 
4.8%
3 10
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
o 20
33.3%
r 20
33.3%
m 10
16.7%
e 10
16.7%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 620
91.2%
Latin 60
 
8.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 416
67.1%
1 145
 
23.4%
2 29
 
4.7%
20
 
3.2%
3 10
 
1.6%
Latin
ValueCountFrequency (%)
o 20
33.3%
r 20
33.3%
m 10
16.7%
e 10
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 416
61.2%
1 145
 
21.3%
2 29
 
4.3%
20
 
2.9%
o 20
 
2.9%
r 20
 
2.9%
3 10
 
1.5%
m 10
 
1.5%
e 10
 
1.5%

qnumberofjobs
Text

MISSING 

Distinct4
Distinct (%)0.6%
Missing293
Missing (%)29.3%
Memory size52.0 KiB
2023-12-09T21:44:55.582730image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length14
Median length5
Mean length4.813295615
Min length1

Characters and Unicode

Total characters3403
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1 job
2nd row1 job
3rd row1 job
4th row1 job
5th row1 job
ValueCountFrequency (%)
1 492
36.3%
job 492
36.3%
0 111
 
8.2%
jobs 104
 
7.7%
2 78
 
5.8%
3 26
 
1.9%
or 26
 
1.9%
more 26
 
1.9%
2023-12-09T21:44:55.866613image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
648
19.0%
o 648
19.0%
j 596
17.5%
b 596
17.5%
1 492
14.5%
0 111
 
3.3%
s 104
 
3.1%
2 78
 
2.3%
r 52
 
1.5%
3 26
 
0.8%
Other values (2) 52
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2048
60.2%
Decimal Number 707
 
20.8%
Space Separator 648
 
19.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 648
31.6%
j 596
29.1%
b 596
29.1%
s 104
 
5.1%
r 52
 
2.5%
m 26
 
1.3%
e 26
 
1.3%
Decimal Number
ValueCountFrequency (%)
1 492
69.6%
0 111
 
15.7%
2 78
 
11.0%
3 26
 
3.7%
Space Separator
ValueCountFrequency (%)
648
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2048
60.2%
Common 1355
39.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 648
31.6%
j 596
29.1%
b 596
29.1%
s 104
 
5.1%
r 52
 
2.5%
m 26
 
1.3%
e 26
 
1.3%
Common
ValueCountFrequency (%)
648
47.8%
1 492
36.3%
0 111
 
8.2%
2 78
 
5.8%
3 26
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3403
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
648
19.0%
o 648
19.0%
j 596
17.5%
b 596
17.5%
1 492
14.5%
0 111
 
3.3%
s 104
 
3.1%
2 78
 
2.3%
r 52
 
1.5%
3 26
 
0.8%
Other values (2) 52
 
1.5%

qworklocation
Text

MISSING 

Distinct10
Distinct (%)1.7%
Missing401
Missing (%)40.1%
Memory size56.8 KiB
2023-12-09T21:44:56.090886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length80
Median length12
Mean length18.48414023
Min length5

Characters and Unicode

Total characters11072
Distinct characters36
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowAt an office
2nd rowAt a school or day care facility
3rd rowAt a store, restaurant, or hotel
4th rowVarying job sites
5th rowFrom home
ValueCountFrequency (%)
at 470
21.2%
office 329
14.9%
an 329
14.9%
a 151
 
6.8%
or 98
 
4.4%
facility 95
 
4.3%
home 60
 
2.7%
school 52
 
2.3%
day 52
 
2.3%
care 52
 
2.3%
Other values (26) 527
23.8%
2023-12-09T21:44:56.441159image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1616
14.6%
o 1002
9.0%
a 967
 
8.7%
t 961
 
8.7%
f 860
 
7.8%
e 823
 
7.4%
i 734
 
6.6%
c 712
 
6.4%
r 482
 
4.4%
A 460
 
4.2%
Other values (26) 2455
22.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8616
77.8%
Space Separator 1616
 
14.6%
Uppercase Letter 599
 
5.4%
Other Punctuation 221
 
2.0%
Open Punctuation 10
 
0.1%
Close Punctuation 10
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1002
11.6%
a 967
11.2%
t 961
11.2%
f 860
10.0%
e 823
9.6%
i 734
8.5%
c 712
8.3%
r 482
 
5.6%
n 452
 
5.2%
h 333
 
3.9%
Other values (13) 1290
15.0%
Uppercase Letter
ValueCountFrequency (%)
A 460
76.8%
F 50
 
8.3%
V 42
 
7.0%
O 36
 
6.0%
I 10
 
1.7%
R 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
/ 86
38.9%
, 72
32.6%
' 43
19.5%
. 20
 
9.0%
Space Separator
ValueCountFrequency (%)
1616
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9215
83.2%
Common 1857
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1002
10.9%
a 967
10.5%
t 961
10.4%
f 860
9.3%
e 823
8.9%
i 734
8.0%
c 712
7.7%
r 482
 
5.2%
A 460
 
5.0%
n 452
 
4.9%
Other values (19) 1762
19.1%
Common
ValueCountFrequency (%)
1616
87.0%
/ 86
 
4.6%
, 72
 
3.9%
' 43
 
2.3%
. 20
 
1.1%
( 10
 
0.5%
) 10
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11072
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1616
14.6%
o 1002
9.0%
a 967
 
8.7%
t 961
 
8.7%
f 860
 
7.8%
e 823
 
7.4%
i 734
 
6.6%
c 712
 
6.4%
r 482
 
4.4%
A 460
 
4.2%
Other values (26) 2455
22.2%

qworkfh
Text

MISSING 

Distinct2
Distinct (%)0.3%
Missing402
Missing (%)40.2%
Memory size59.8 KiB
2023-12-09T21:44:56.620187image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length25
Median length25
Mean length23.64548495
Min length19

Characters and Unicode

Total characters14140
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo, do not work from home
2nd rowNo, do not work from home
3rd rowNo, do not work from home
4th rowNo, do not work from home
5th rowYes, work from home
ValueCountFrequency (%)
work 598
18.0%
from 598
18.0%
home 598
18.0%
no 463
14.0%
do 463
14.0%
not 463
14.0%
yes 135
 
4.1%
2023-12-09T21:44:56.908954image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 3183
22.5%
2720
19.2%
r 1196
 
8.5%
m 1196
 
8.5%
e 733
 
5.2%
, 598
 
4.2%
w 598
 
4.2%
k 598
 
4.2%
f 598
 
4.2%
h 598
 
4.2%
Other values (6) 2122
15.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10224
72.3%
Space Separator 2720
 
19.2%
Other Punctuation 598
 
4.2%
Uppercase Letter 598
 
4.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 3183
31.1%
r 1196
 
11.7%
m 1196
 
11.7%
e 733
 
7.2%
w 598
 
5.8%
k 598
 
5.8%
f 598
 
5.8%
h 598
 
5.8%
d 463
 
4.5%
n 463
 
4.5%
Other values (2) 598
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
N 463
77.4%
Y 135
 
22.6%
Space Separator
ValueCountFrequency (%)
2720
100.0%
Other Punctuation
ValueCountFrequency (%)
, 598
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10822
76.5%
Common 3318
 
23.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 3183
29.4%
r 1196
 
11.1%
m 1196
 
11.1%
e 733
 
6.8%
w 598
 
5.5%
k 598
 
5.5%
f 598
 
5.5%
h 598
 
5.5%
N 463
 
4.3%
d 463
 
4.3%
Other values (4) 1196
 
11.1%
Common
ValueCountFrequency (%)
2720
82.0%
, 598
 
18.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 3183
22.5%
2720
19.2%
r 1196
 
8.5%
m 1196
 
8.5%
e 733
 
5.2%
, 598
 
4.2%
w 598
 
4.2%
k 598
 
4.2%
f 598
 
4.2%
h 598
 
4.2%
Other values (6) 2122
15.0%

qborough_work1
Text

MISSING 

Distinct5
Distinct (%)1.1%
Missing540
Missing (%)54.0%
Memory size46.5 KiB
2023-12-09T21:44:57.088756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length13
Median length9
Mean length8.658695652
Min length6

Characters and Unicode

Total characters3983
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowManhattan
2nd rowBrooklyn
3rd rowManhattan
4th rowManhattan
5th rowManhattan
ValueCountFrequency (%)
manhattan 272
52.4%
queens 74
 
14.3%
brooklyn 55
 
10.6%
staten 30
 
5.8%
island 30
 
5.8%
the 29
 
5.6%
bronx 29
 
5.6%
2023-12-09T21:44:57.404317image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 876
22.0%
n 762
19.1%
t 604
15.2%
h 301
 
7.6%
M 272
 
6.8%
e 207
 
5.2%
o 139
 
3.5%
s 104
 
2.6%
l 85
 
2.1%
r 84
 
2.1%
Other values (11) 549
13.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3405
85.5%
Uppercase Letter 519
 
13.0%
Space Separator 59
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 876
25.7%
n 762
22.4%
t 604
17.7%
h 301
 
8.8%
e 207
 
6.1%
o 139
 
4.1%
s 104
 
3.1%
l 85
 
2.5%
r 84
 
2.5%
u 74
 
2.2%
Other values (4) 169
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
M 272
52.4%
B 84
 
16.2%
Q 74
 
14.3%
S 30
 
5.8%
I 30
 
5.8%
T 29
 
5.6%
Space Separator
ValueCountFrequency (%)
59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3924
98.5%
Common 59
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 876
22.3%
n 762
19.4%
t 604
15.4%
h 301
 
7.7%
M 272
 
6.9%
e 207
 
5.3%
o 139
 
3.5%
s 104
 
2.7%
l 85
 
2.2%
r 84
 
2.1%
Other values (10) 490
12.5%
Common
ValueCountFrequency (%)
59
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3983
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 876
22.0%
n 762
19.1%
t 604
15.2%
h 301
 
7.6%
M 272
 
6.8%
e 207
 
5.2%
o 139
 
3.5%
s 104
 
2.6%
l 85
 
2.1%
r 84
 
2.1%
Other values (11) 549
13.8%

qntacode_work
Text

MISSING 

Distinct123
Distinct (%)26.7%
Missing540
Missing (%)54.0%
Memory size44.4 KiB
2023-12-09T21:44:57.763715image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1840
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)11.5%

Sample

1st rowMN40
2nd rowBK17
3rd rowMN23
4th rowMN03
5th rowMN17
ValueCountFrequency (%)
mn17 78
 
17.0%
mn25 20
 
4.3%
mn24 19
 
4.1%
mn19 16
 
3.5%
mn13 14
 
3.0%
mn40 12
 
2.6%
mn36 11
 
2.4%
mn23 11
 
2.4%
mn12 10
 
2.2%
mn14 9
 
2.0%
Other values (113) 260
56.5%
2023-12-09T21:44:58.244939image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 346
18.8%
M 272
14.8%
1 191
10.4%
2 129
 
7.0%
3 109
 
5.9%
7 108
 
5.9%
4 92
 
5.0%
B 84
 
4.6%
0 75
 
4.1%
Q 74
 
4.0%
Other values (8) 360
19.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 920
50.0%
Decimal Number 920
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 191
20.8%
2 129
14.0%
3 109
11.8%
7 108
11.7%
4 92
10.0%
0 75
 
8.2%
9 68
 
7.4%
5 66
 
7.2%
6 57
 
6.2%
8 25
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
N 346
37.6%
M 272
29.6%
B 84
 
9.1%
Q 74
 
8.0%
K 55
 
6.0%
S 30
 
3.3%
I 30
 
3.3%
X 29
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 920
50.0%
Common 920
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 191
20.8%
2 129
14.0%
3 109
11.8%
7 108
11.7%
4 92
10.0%
0 75
 
8.2%
9 68
 
7.4%
5 66
 
7.2%
6 57
 
6.2%
8 25
 
2.7%
Latin
ValueCountFrequency (%)
N 346
37.6%
M 272
29.6%
B 84
 
9.1%
Q 74
 
8.0%
K 55
 
6.0%
S 30
 
3.3%
I 30
 
3.3%
X 29
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 346
18.8%
M 272
14.8%
1 191
10.4%
2 129
 
7.0%
3 109
 
5.9%
7 108
 
5.9%
4 92
 
5.0%
B 84
 
4.6%
0 75
 
4.1%
Q 74
 
4.0%
Other values (8) 360
19.6%

qtimework
Text

MISSING 

Distinct222
Distinct (%)40.7%
Missing454
Missing (%)45.4%
Memory size49.1 KiB
2023-12-09T21:44:58.585501image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length255
Median length191
Mean length7.730769231
Min length1

Characters and Unicode

Total characters4221
Distinct characters70
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)30.4%

Sample

1st row8:15 AM
2nd row6:45AM
3rd row10a
4th rowTotally varies, I freelance
5th row8am
ValueCountFrequency (%)
am 171
 
16.8%
9am 62
 
6.1%
8am 50
 
4.9%
9:00 28
 
2.7%
8:00 28
 
2.7%
7am 27
 
2.6%
to 20
 
2.0%
7:00 20
 
2.0%
pm 19
 
1.9%
i 17
 
1.7%
Other values (274) 578
56.7%
2023-12-09T21:44:59.073394image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
474
 
11.2%
0 383
 
9.1%
a 344
 
8.1%
m 316
 
7.5%
M 224
 
5.3%
A 212
 
5.0%
: 211
 
5.0%
e 167
 
4.0%
8 140
 
3.3%
9 130
 
3.1%
Other values (60) 1620
38.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1849
43.8%
Decimal Number 1031
24.4%
Uppercase Letter 567
 
13.4%
Space Separator 474
 
11.2%
Other Punctuation 281
 
6.7%
Dash Punctuation 12
 
0.3%
Control 3
 
0.1%
Other Symbol 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 224
39.5%
A 212
37.4%
P 24
 
4.2%
I 23
 
4.1%
N 10
 
1.8%
L 9
 
1.6%
Y 7
 
1.2%
E 7
 
1.2%
O 6
 
1.1%
T 5
 
0.9%
Other values (15) 40
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
a 344
18.6%
m 316
17.1%
e 167
9.0%
o 112
 
6.1%
t 108
 
5.8%
r 93
 
5.0%
n 93
 
5.0%
i 89
 
4.8%
s 71
 
3.8%
l 60
 
3.2%
Other values (13) 396
21.4%
Decimal Number
ValueCountFrequency (%)
0 383
37.1%
8 140
 
13.6%
9 130
 
12.6%
7 89
 
8.6%
3 85
 
8.2%
1 73
 
7.1%
5 51
 
4.9%
6 39
 
3.8%
4 30
 
2.9%
2 11
 
1.1%
Other Punctuation
ValueCountFrequency (%)
: 211
75.1%
. 57
 
20.3%
, 8
 
2.8%
; 4
 
1.4%
' 1
 
0.4%
Space Separator
ValueCountFrequency (%)
474
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Other Symbol
ValueCountFrequency (%)
� 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Math Symbol
ValueCountFrequency (%)
< 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2416
57.2%
Common 1805
42.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 344
14.2%
m 316
13.1%
M 224
 
9.3%
A 212
 
8.8%
e 167
 
6.9%
o 112
 
4.6%
t 108
 
4.5%
r 93
 
3.8%
n 93
 
3.8%
i 89
 
3.7%
Other values (38) 658
27.2%
Common
ValueCountFrequency (%)
474
26.3%
0 383
21.2%
: 211
11.7%
8 140
 
7.8%
9 130
 
7.2%
7 89
 
4.9%
3 85
 
4.7%
1 73
 
4.0%
. 57
 
3.2%
5 51
 
2.8%
Other values (12) 112
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4220
> 99.9%
Specials 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
474
 
11.2%
0 383
 
9.1%
a 344
 
8.2%
m 316
 
7.5%
M 224
 
5.3%
A 212
 
5.0%
: 211
 
5.0%
e 167
 
4.0%
8 140
 
3.3%
9 130
 
3.1%
Other values (59) 1619
38.4%
Specials
ValueCountFrequency (%)
� 1
100.0%

qtimehome
Text

MISSING 

Distinct204
Distinct (%)37.4%
Missing454
Missing (%)45.4%
Memory size48.5 KiB
2023-12-09T21:44:59.504282image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length255
Median length133
Mean length6.65018315
Min length1

Characters and Unicode

Total characters3631
Distinct characters67
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)26.0%

Sample

1st row7:00 PM
2nd row5"30PM
3rd row1030p
4th rowVaries
5th row6pm or 11pm
ValueCountFrequency (%)
pm 174
 
19.2%
6pm 57
 
6.3%
7pm 42
 
4.6%
6:00 33
 
3.7%
5pm 23
 
2.5%
5:00 17
 
1.9%
5:30pm 17
 
1.9%
7:00 14
 
1.5%
6:30 14
 
1.5%
p.m 13
 
1.4%
Other values (235) 500
55.3%
2023-12-09T21:45:00.092749image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 385
 
10.6%
359
 
9.9%
m 300
 
8.3%
p 264
 
7.3%
M 226
 
6.2%
: 217
 
6.0%
P 215
 
5.9%
6 155
 
4.3%
3 121
 
3.3%
5 119
 
3.3%
Other values (57) 1270
35.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1391
38.3%
Decimal Number 1053
29.0%
Uppercase Letter 537
 
14.8%
Space Separator 359
 
9.9%
Other Punctuation 282
 
7.8%
Dash Punctuation 5
 
0.1%
Control 3
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m 300
21.6%
p 264
19.0%
e 112
 
8.1%
a 79
 
5.7%
o 79
 
5.7%
t 74
 
5.3%
n 69
 
5.0%
i 62
 
4.5%
r 60
 
4.3%
s 47
 
3.4%
Other values (14) 245
17.6%
Uppercase Letter
ValueCountFrequency (%)
M 226
42.1%
P 215
40.0%
A 19
 
3.5%
I 17
 
3.2%
N 8
 
1.5%
Y 6
 
1.1%
E 6
 
1.1%
V 5
 
0.9%
D 4
 
0.7%
R 4
 
0.7%
Other values (14) 27
 
5.0%
Decimal Number
ValueCountFrequency (%)
0 385
36.6%
6 155
14.7%
3 121
 
11.5%
5 119
 
11.3%
7 90
 
8.5%
1 54
 
5.1%
4 52
 
4.9%
2 31
 
2.9%
8 29
 
2.8%
9 17
 
1.6%
Other Punctuation
ValueCountFrequency (%)
: 217
77.0%
. 55
 
19.5%
, 6
 
2.1%
; 3
 
1.1%
" 1
 
0.4%
Space Separator
ValueCountFrequency (%)
359
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Other Symbol
ValueCountFrequency (%)
� 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1928
53.1%
Common 1703
46.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 300
15.6%
p 264
13.7%
M 226
11.7%
P 215
11.2%
e 112
 
5.8%
a 79
 
4.1%
o 79
 
4.1%
t 74
 
3.8%
n 69
 
3.6%
i 62
 
3.2%
Other values (38) 448
23.2%
Common
ValueCountFrequency (%)
0 385
22.6%
359
21.1%
: 217
12.7%
6 155
9.1%
3 121
 
7.1%
5 119
 
7.0%
7 90
 
5.3%
. 55
 
3.2%
1 54
 
3.2%
4 52
 
3.1%
Other values (9) 96
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3630
> 99.9%
Specials 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 385
 
10.6%
359
 
9.9%
m 300
 
8.3%
p 264
 
7.3%
M 226
 
6.2%
: 217
 
6.0%
P 215
 
5.9%
6 155
 
4.3%
3 121
 
3.3%
5 119
 
3.3%
Other values (56) 1269
35.0%
Specials
ValueCountFrequency (%)
� 1
100.0%

qborough_work2
Text

MISSING 

Distinct5
Distinct (%)6.3%
Missing921
Missing (%)92.1%
Memory size34.0 KiB
2023-12-09T21:45:00.274416image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length13
Median length9
Mean length8.620253165
Min length6

Characters and Unicode

Total characters681
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowManhattan
2nd rowManhattan
3rd rowBrooklyn
4th rowManhattan
5th rowBrooklyn
ValueCountFrequency (%)
manhattan 37
39.8%
brooklyn 15
16.1%
queens 13
 
14.0%
the 8
 
8.6%
bronx 8
 
8.6%
staten 6
 
6.5%
island 6
 
6.5%
2023-12-09T21:45:00.571732image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 123
18.1%
n 122
17.9%
t 86
12.6%
h 45
 
6.6%
e 40
 
5.9%
o 38
 
5.6%
M 37
 
5.4%
B 23
 
3.4%
r 23
 
3.4%
l 21
 
3.1%
Other values (11) 123
18.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 574
84.3%
Uppercase Letter 93
 
13.7%
Space Separator 14
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 123
21.4%
n 122
21.3%
t 86
15.0%
h 45
 
7.8%
e 40
 
7.0%
o 38
 
6.6%
r 23
 
4.0%
l 21
 
3.7%
s 19
 
3.3%
y 15
 
2.6%
Other values (4) 42
 
7.3%
Uppercase Letter
ValueCountFrequency (%)
M 37
39.8%
B 23
24.7%
Q 13
 
14.0%
T 8
 
8.6%
S 6
 
6.5%
I 6
 
6.5%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 667
97.9%
Common 14
 
2.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 123
18.4%
n 122
18.3%
t 86
12.9%
h 45
 
6.7%
e 40
 
6.0%
o 38
 
5.7%
M 37
 
5.5%
B 23
 
3.4%
r 23
 
3.4%
l 21
 
3.1%
Other values (10) 109
16.3%
Common
ValueCountFrequency (%)
14
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 681
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 123
18.1%
n 122
17.9%
t 86
12.6%
h 45
 
6.6%
e 40
 
5.9%
o 38
 
5.6%
M 37
 
5.4%
B 23
 
3.4%
r 23
 
3.4%
l 21
 
3.1%
Other values (11) 123
18.1%

qntacode_work2
Text

MISSING 

Distinct50
Distinct (%)63.3%
Missing921
Missing (%)92.1%
Memory size33.6 KiB
2023-12-09T21:45:00.818745image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters316
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)46.8%

Sample

1st rowMN27
2nd rowMN35
3rd rowBK61
4th rowMN17
5th rowBK75
ValueCountFrequency (%)
mn17 8
 
10.1%
mn24 5
 
6.3%
bk61 4
 
5.1%
mn15 4
 
5.1%
mn99 3
 
3.8%
si24 3
 
3.8%
mn14 3
 
3.8%
bx49 2
 
2.5%
bk99 2
 
2.5%
qn22 2
 
2.5%
Other values (40) 43
54.4%
2023-12-09T21:45:01.179929image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 50
15.8%
M 37
11.7%
1 29
9.2%
B 23
 
7.3%
4 21
 
6.6%
3 19
 
6.0%
2 19
 
6.0%
9 18
 
5.7%
7 16
 
5.1%
K 15
 
4.7%
Other values (8) 69
21.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 158
50.0%
Decimal Number 158
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 29
18.4%
4 21
13.3%
3 19
12.0%
2 19
12.0%
9 18
11.4%
7 16
10.1%
5 13
8.2%
0 11
 
7.0%
6 8
 
5.1%
8 4
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
N 50
31.6%
M 37
23.4%
B 23
14.6%
K 15
 
9.5%
Q 13
 
8.2%
X 8
 
5.1%
S 6
 
3.8%
I 6
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 158
50.0%
Common 158
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 29
18.4%
4 21
13.3%
3 19
12.0%
2 19
12.0%
9 18
11.4%
7 16
10.1%
5 13
8.2%
0 11
 
7.0%
6 8
 
5.1%
8 4
 
2.5%
Latin
ValueCountFrequency (%)
N 50
31.6%
M 37
23.4%
B 23
14.6%
K 15
 
9.5%
Q 13
 
8.2%
X 8
 
5.1%
S 6
 
3.8%
I 6
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 316
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 50
15.8%
M 37
11.7%
1 29
9.2%
B 23
 
7.3%
4 21
 
6.6%
3 19
 
6.0%
2 19
 
6.0%
9 18
 
5.7%
7 16
 
5.1%
K 15
 
4.7%
Other values (8) 69
21.8%

qtimework2
Text

MISSING 

Distinct70
Distinct (%)77.8%
Missing910
Missing (%)91.0%
Memory size34.4 KiB
2023-12-09T21:45:01.531752image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length255
Median length28
Mean length9.044444444
Min length1

Characters and Unicode

Total characters814
Distinct characters60
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)62.2%

Sample

1st row10am
2nd row8:00 PM
3rd rowVaRIOUS tIMES
4th rowIt varies
5th rowAM
ValueCountFrequency (%)
pm 14
 
7.4%
am 11
 
5.8%
10am 4
 
2.1%
in 4
 
2.1%
2pm 4
 
2.1%
i 4
 
2.1%
7pm 4
 
2.1%
varies 4
 
2.1%
6pm 4
 
2.1%
9:00 3
 
1.6%
Other values (103) 133
70.4%
2023-12-09T21:45:02.017125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
 
12.2%
m 48
 
5.9%
a 46
 
5.7%
0 45
 
5.5%
e 41
 
5.0%
o 40
 
4.9%
M 38
 
4.7%
t 32
 
3.9%
n 31
 
3.8%
p 28
 
3.4%
Other values (50) 366
45.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 425
52.2%
Decimal Number 133
 
16.3%
Uppercase Letter 121
 
14.9%
Space Separator 99
 
12.2%
Other Punctuation 33
 
4.1%
Dash Punctuation 3
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m 48
11.3%
a 46
10.8%
e 41
9.6%
o 40
9.4%
t 32
 
7.5%
n 31
 
7.3%
p 28
 
6.6%
s 26
 
6.1%
i 24
 
5.6%
r 21
 
4.9%
Other values (15) 88
20.7%
Uppercase Letter
ValueCountFrequency (%)
M 38
31.4%
P 24
19.8%
A 16
13.2%
I 9
 
7.4%
S 5
 
4.1%
Y 4
 
3.3%
E 3
 
2.5%
O 3
 
2.5%
R 3
 
2.5%
N 3
 
2.5%
Other values (8) 13
 
10.7%
Decimal Number
ValueCountFrequency (%)
0 45
33.8%
1 16
 
12.0%
2 13
 
9.8%
7 12
 
9.0%
6 12
 
9.0%
3 12
 
9.0%
8 8
 
6.0%
9 6
 
4.5%
5 6
 
4.5%
4 3
 
2.3%
Other Punctuation
ValueCountFrequency (%)
: 20
60.6%
. 8
 
24.2%
, 3
 
9.1%
; 1
 
3.0%
\ 1
 
3.0%
Space Separator
ValueCountFrequency (%)
99
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 546
67.1%
Common 268
32.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 48
 
8.8%
a 46
 
8.4%
e 41
 
7.5%
o 40
 
7.3%
M 38
 
7.0%
t 32
 
5.9%
n 31
 
5.7%
p 28
 
5.1%
s 26
 
4.8%
i 24
 
4.4%
Other values (33) 192
35.2%
Common
ValueCountFrequency (%)
99
36.9%
0 45
16.8%
: 20
 
7.5%
1 16
 
6.0%
2 13
 
4.9%
7 12
 
4.5%
6 12
 
4.5%
3 12
 
4.5%
8 8
 
3.0%
. 8
 
3.0%
Other values (7) 23
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 814
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
99
 
12.2%
m 48
 
5.9%
a 46
 
5.7%
0 45
 
5.5%
e 41
 
5.0%
o 40
 
4.9%
M 38
 
4.7%
t 32
 
3.9%
n 31
 
3.8%
p 28
 
3.4%
Other values (50) 366
45.0%

qtimehome2
Text

MISSING 

Distinct67
Distinct (%)74.4%
Missing910
Missing (%)91.0%
Memory size34.2 KiB
2023-12-09T21:45:02.301267image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length40
Median length28
Mean length6.9
Min length1

Characters and Unicode

Total characters621
Distinct characters54
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)55.6%

Sample

1st row3pm
2nd row12:00 AM
3rd rowVariuos times
4th rowIt varies
5th rowPM
ValueCountFrequency (%)
pm 21
 
13.7%
am 6
 
3.9%
varies 5
 
3.3%
5pm 4
 
2.6%
6pm 4
 
2.6%
7pm 3
 
2.0%
i 3
 
2.0%
p.m 3
 
2.0%
11pm 3
 
2.0%
9:00 3
 
2.0%
Other values (72) 98
64.1%
2023-12-09T21:45:02.732563image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
10.1%
0 53
 
8.5%
m 45
 
7.2%
p 38
 
6.1%
M 35
 
5.6%
P 27
 
4.3%
: 26
 
4.2%
e 26
 
4.2%
1 25
 
4.0%
o 24
 
3.9%
Other values (44) 259
41.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 274
44.1%
Decimal Number 146
23.5%
Uppercase Letter 102
 
16.4%
Space Separator 63
 
10.1%
Other Punctuation 34
 
5.5%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m 45
16.4%
p 38
13.9%
e 26
9.5%
o 24
8.8%
i 19
 
6.9%
n 17
 
6.2%
r 16
 
5.8%
t 15
 
5.5%
a 13
 
4.7%
s 10
 
3.6%
Other values (13) 51
18.6%
Uppercase Letter
ValueCountFrequency (%)
M 35
34.3%
P 27
26.5%
A 12
 
11.8%
I 6
 
5.9%
Y 3
 
2.9%
N 3
 
2.9%
V 3
 
2.9%
O 2
 
2.0%
L 2
 
2.0%
R 2
 
2.0%
Other values (7) 7
 
6.9%
Decimal Number
ValueCountFrequency (%)
0 53
36.3%
1 25
17.1%
3 15
 
10.3%
5 10
 
6.8%
9 8
 
5.5%
2 8
 
5.5%
7 7
 
4.8%
4 7
 
4.8%
8 7
 
4.8%
6 6
 
4.1%
Other Punctuation
ValueCountFrequency (%)
: 26
76.5%
. 8
 
23.5%
Space Separator
ValueCountFrequency (%)
63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 376
60.5%
Common 245
39.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 45
 
12.0%
p 38
 
10.1%
M 35
 
9.3%
P 27
 
7.2%
e 26
 
6.9%
o 24
 
6.4%
i 19
 
5.1%
n 17
 
4.5%
r 16
 
4.3%
t 15
 
4.0%
Other values (30) 114
30.3%
Common
ValueCountFrequency (%)
63
25.7%
0 53
21.6%
: 26
10.6%
1 25
 
10.2%
3 15
 
6.1%
5 10
 
4.1%
9 8
 
3.3%
. 8
 
3.3%
2 8
 
3.3%
7 7
 
2.9%
Other values (4) 22
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 621
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
 
10.1%
0 53
 
8.5%
m 45
 
7.2%
p 38
 
6.1%
M 35
 
5.6%
P 27
 
4.3%
: 26
 
4.2%
e 26
 
4.2%
1 25
 
4.0%
o 24
 
3.9%
Other values (44) 259
41.7%

qborough_work3
Text

MISSING 

Distinct5
Distinct (%)21.7%
Missing977
Missing (%)97.7%
Memory size32.1 KiB
2023-12-09T21:45:02.908076image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length13
Median length9
Mean length8.956521739
Min length6

Characters and Unicode

Total characters206
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBrooklyn
2nd rowManhattan
3rd rowBrooklyn
4th rowManhattan
5th rowBrooklyn
ValueCountFrequency (%)
manhattan 9
32.1%
brooklyn 7
25.0%
staten 3
 
10.7%
island 3
 
10.7%
the 2
 
7.1%
bronx 2
 
7.1%
queens 2
 
7.1%
2023-12-09T21:45:03.211440image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 35
17.0%
a 33
16.0%
t 24
11.7%
o 16
 
7.8%
h 11
 
5.3%
l 10
 
4.9%
M 9
 
4.4%
B 9
 
4.4%
r 9
 
4.4%
e 9
 
4.4%
Other values (11) 41
19.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 173
84.0%
Uppercase Letter 28
 
13.6%
Space Separator 5
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 35
20.2%
a 33
19.1%
t 24
13.9%
o 16
9.2%
h 11
 
6.4%
l 10
 
5.8%
r 9
 
5.2%
e 9
 
5.2%
y 7
 
4.0%
k 7
 
4.0%
Other values (4) 12
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
M 9
32.1%
B 9
32.1%
S 3
 
10.7%
I 3
 
10.7%
T 2
 
7.1%
Q 2
 
7.1%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 201
97.6%
Common 5
 
2.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 35
17.4%
a 33
16.4%
t 24
11.9%
o 16
8.0%
h 11
 
5.5%
l 10
 
5.0%
M 9
 
4.5%
B 9
 
4.5%
r 9
 
4.5%
e 9
 
4.5%
Other values (10) 36
17.9%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 206
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 35
17.0%
a 33
16.0%
t 24
11.7%
o 16
 
7.8%
h 11
 
5.3%
l 10
 
4.9%
M 9
 
4.4%
B 9
 
4.4%
r 9
 
4.4%
e 9
 
4.4%
Other values (11) 41
19.9%

qntacode_work3
Text

MISSING 

Distinct20
Distinct (%)87.0%
Missing977
Missing (%)97.7%
Memory size32.0 KiB
2023-12-09T21:45:03.420664image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters92
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)73.9%

Sample

1st rowBK61
2nd rowMN35
3rd rowBK75
4th rowMN01
5th rowBK63
ValueCountFrequency (%)
bk75 2
 
8.7%
mn99 2
 
8.7%
si24 2
 
8.7%
mn20 1
 
4.3%
bx06 1
 
4.3%
qn54 1
 
4.3%
qn38 1
 
4.3%
mn24 1
 
4.3%
mn09 1
 
4.3%
mn17 1
 
4.3%
Other values (10) 10
43.5%
2023-12-09T21:45:03.737348image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 11
12.0%
M 9
 
9.8%
B 9
 
9.8%
K 7
 
7.6%
2 6
 
6.5%
0 6
 
6.5%
4 5
 
5.4%
7 5
 
5.4%
9 5
 
5.4%
3 5
 
5.4%
Other values (8) 24
26.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 46
50.0%
Decimal Number 46
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 6
13.0%
0 6
13.0%
4 5
10.9%
7 5
10.9%
9 5
10.9%
3 5
10.9%
6 5
10.9%
5 4
8.7%
1 4
8.7%
8 1
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
N 11
23.9%
M 9
19.6%
B 9
19.6%
K 7
15.2%
S 3
 
6.5%
I 3
 
6.5%
X 2
 
4.3%
Q 2
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 46
50.0%
Common 46
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 6
13.0%
0 6
13.0%
4 5
10.9%
7 5
10.9%
9 5
10.9%
3 5
10.9%
6 5
10.9%
5 4
8.7%
1 4
8.7%
8 1
 
2.2%
Latin
ValueCountFrequency (%)
N 11
23.9%
M 9
19.6%
B 9
19.6%
K 7
15.2%
S 3
 
6.5%
I 3
 
6.5%
X 2
 
4.3%
Q 2
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 11
12.0%
M 9
 
9.8%
B 9
 
9.8%
K 7
 
7.6%
2 6
 
6.5%
0 6
 
6.5%
4 5
 
5.4%
7 5
 
5.4%
9 5
 
5.4%
3 5
 
5.4%
Other values (8) 24
26.1%

qtimework3
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing977
Missing (%)97.7%
Memory size32.1 KiB
2023-12-09T21:45:03.975316image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length34
Median length24
Mean length9.347826087
Min length2

Characters and Unicode

Total characters215
Distinct characters50
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st rowVarious hours
2nd rowIt varies
3rd rowAM
4th row10am
5th row2:00 PM
ValueCountFrequency (%)
am 5
 
9.6%
pm 4
 
7.7%
p.m 2
 
3.8%
place 2
 
3.8%
6:00 2
 
3.8%
work 2
 
3.8%
8:00 2
 
3.8%
i 2
 
3.8%
5:00 2
 
3.8%
no 1
 
1.9%
Other values (28) 28
53.8%
2023-12-09T21:45:04.353853image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
13.5%
0 18
 
8.4%
M 10
 
4.7%
A 9
 
4.2%
o 9
 
4.2%
e 8
 
3.7%
: 8
 
3.7%
m 8
 
3.7%
n 7
 
3.3%
i 7
 
3.3%
Other values (40) 102
47.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 91
42.3%
Uppercase Letter 47
21.9%
Decimal Number 33
 
15.3%
Space Separator 29
 
13.5%
Other Punctuation 15
 
7.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 9
9.9%
e 8
 
8.8%
m 8
 
8.8%
n 7
 
7.7%
i 7
 
7.7%
s 7
 
7.7%
r 7
 
7.7%
a 7
 
7.7%
p 6
 
6.6%
t 4
 
4.4%
Other values (11) 21
23.1%
Uppercase Letter
ValueCountFrequency (%)
M 10
21.3%
A 9
19.1%
P 6
12.8%
I 3
 
6.4%
R 2
 
4.3%
E 2
 
4.3%
V 2
 
4.3%
O 2
 
4.3%
D 2
 
4.3%
N 2
 
4.3%
Other values (7) 7
14.9%
Decimal Number
ValueCountFrequency (%)
0 18
54.5%
6 4
 
12.1%
8 3
 
9.1%
2 2
 
6.1%
3 2
 
6.1%
5 2
 
6.1%
1 1
 
3.0%
9 1
 
3.0%
Other Punctuation
ValueCountFrequency (%)
: 8
53.3%
. 6
40.0%
' 1
 
6.7%
Space Separator
ValueCountFrequency (%)
29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 138
64.2%
Common 77
35.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 10
 
7.2%
A 9
 
6.5%
o 9
 
6.5%
e 8
 
5.8%
m 8
 
5.8%
n 7
 
5.1%
i 7
 
5.1%
s 7
 
5.1%
r 7
 
5.1%
a 7
 
5.1%
Other values (28) 59
42.8%
Common
ValueCountFrequency (%)
29
37.7%
0 18
23.4%
: 8
 
10.4%
. 6
 
7.8%
6 4
 
5.2%
8 3
 
3.9%
2 2
 
2.6%
3 2
 
2.6%
5 2
 
2.6%
1 1
 
1.3%
Other values (2) 2
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 215
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29
 
13.5%
0 18
 
8.4%
M 10
 
4.7%
A 9
 
4.2%
o 9
 
4.2%
e 8
 
3.7%
: 8
 
3.7%
m 8
 
3.7%
n 7
 
3.3%
i 7
 
3.3%
Other values (40) 102
47.4%

qtimehome3
Text

MISSING 

Distinct20
Distinct (%)87.0%
Missing977
Missing (%)97.7%
Memory size32.1 KiB
2023-12-09T21:45:04.562576image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length31
Median length24
Mean length8.869565217
Min length2

Characters and Unicode

Total characters204
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)73.9%

Sample

1st rowVarious times
2nd rowVaries
3rd rowPM
4th row1pm
5th row1:00 PM
ValueCountFrequency (%)
pm 9
 
17.6%
1:00 3
 
5.9%
varies 2
 
3.9%
work 2
 
3.9%
12:00 2
 
3.9%
p.m 2
 
3.9%
place 2
 
3.9%
i 2
 
3.9%
10:00 2
 
3.9%
1pm 1
 
2.0%
Other values (24) 24
47.1%
2023-12-09T21:45:04.922262image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28
 
13.7%
0 19
 
9.3%
o 13
 
6.4%
M 10
 
4.9%
1 9
 
4.4%
r 9
 
4.4%
e 9
 
4.4%
: 9
 
4.4%
m 9
 
4.4%
P 8
 
3.9%
Other values (30) 81
39.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 100
49.0%
Decimal Number 36
 
17.6%
Space Separator 28
 
13.7%
Uppercase Letter 26
 
12.7%
Other Punctuation 14
 
6.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 13
13.0%
r 9
 
9.0%
e 9
 
9.0%
m 9
 
9.0%
p 8
 
8.0%
a 8
 
8.0%
i 6
 
6.0%
n 6
 
6.0%
s 4
 
4.0%
t 4
 
4.0%
Other values (12) 24
24.0%
Decimal Number
ValueCountFrequency (%)
0 19
52.8%
1 9
25.0%
2 3
 
8.3%
3 2
 
5.6%
9 1
 
2.8%
6 1
 
2.8%
7 1
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
M 10
38.5%
P 8
30.8%
V 2
 
7.7%
A 2
 
7.7%
I 2
 
7.7%
N 1
 
3.8%
Y 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
: 9
64.3%
. 4
28.6%
' 1
 
7.1%
Space Separator
ValueCountFrequency (%)
28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 126
61.8%
Common 78
38.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 13
 
10.3%
M 10
 
7.9%
r 9
 
7.1%
e 9
 
7.1%
m 9
 
7.1%
P 8
 
6.3%
p 8
 
6.3%
a 8
 
6.3%
i 6
 
4.8%
n 6
 
4.8%
Other values (19) 40
31.7%
Common
ValueCountFrequency (%)
28
35.9%
0 19
24.4%
1 9
 
11.5%
: 9
 
11.5%
. 4
 
5.1%
2 3
 
3.8%
3 2
 
2.6%
9 1
 
1.3%
' 1
 
1.3%
6 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 204
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28
 
13.7%
0 19
 
9.3%
o 13
 
6.4%
M 10
 
4.9%
1 9
 
4.4%
r 9
 
4.4%
e 9
 
4.4%
: 9
 
4.4%
m 9
 
4.4%
P 8
 
3.9%
Other values (30) 81
39.7%

qworktravelcode01
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size46.0 KiB
2023-12-09T21:45:05.052018image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.276867031
Min length2

Characters and Unicode

Total characters1250
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 397
72.3%
yes 152
 
27.7%
2023-12-09T21:45:05.289249image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 397
31.8%
o 397
31.8%
Y 152
 
12.2%
e 152
 
12.2%
s 152
 
12.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 701
56.1%
Uppercase Letter 549
43.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 397
56.6%
e 152
 
21.7%
s 152
 
21.7%
Uppercase Letter
ValueCountFrequency (%)
N 397
72.3%
Y 152
 
27.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 1250
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 397
31.8%
o 397
31.8%
Y 152
 
12.2%
e 152
 
12.2%
s 152
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 397
31.8%
o 397
31.8%
Y 152
 
12.2%
e 152
 
12.2%
s 152
 
12.2%

qworktravelcode02
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size46.1 KiB
2023-12-09T21:45:05.428647image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.499089253
Min length2

Characters and Unicode

Total characters1372
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowYes
5th rowYes
ValueCountFrequency (%)
no 275
50.1%
yes 274
49.9%
2023-12-09T21:45:05.683482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 275
20.0%
o 275
20.0%
Y 274
20.0%
e 274
20.0%
s 274
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 823
60.0%
Uppercase Letter 549
40.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 275
33.4%
e 274
33.3%
s 274
33.3%
Uppercase Letter
ValueCountFrequency (%)
N 275
50.1%
Y 274
49.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 1372
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 275
20.0%
o 275
20.0%
Y 274
20.0%
e 274
20.0%
s 274
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 275
20.0%
o 275
20.0%
Y 274
20.0%
e 274
20.0%
s 274
20.0%

qworktravelcode03
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:05.797441image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.149362477
Min length2

Characters and Unicode

Total characters1180
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 467
85.1%
yes 82
 
14.9%
2023-12-09T21:45:06.018875image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 467
39.6%
o 467
39.6%
Y 82
 
6.9%
e 82
 
6.9%
s 82
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 631
53.5%
Uppercase Letter 549
46.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 467
74.0%
e 82
 
13.0%
s 82
 
13.0%
Uppercase Letter
ValueCountFrequency (%)
N 467
85.1%
Y 82
 
14.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 1180
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 467
39.6%
o 467
39.6%
Y 82
 
6.9%
e 82
 
6.9%
s 82
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 467
39.6%
o 467
39.6%
Y 82
 
6.9%
e 82
 
6.9%
s 82
 
6.9%

qworktravelcode04
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:06.128964image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.027322404
Min length2

Characters and Unicode

Total characters1113
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 534
97.3%
yes 15
 
2.7%
2023-12-09T21:45:06.352141image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 534
48.0%
o 534
48.0%
Y 15
 
1.3%
e 15
 
1.3%
s 15
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 564
50.7%
Uppercase Letter 549
49.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 534
94.7%
e 15
 
2.7%
s 15
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
N 534
97.3%
Y 15
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 1113
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 534
48.0%
o 534
48.0%
Y 15
 
1.3%
e 15
 
1.3%
s 15
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1113
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 534
48.0%
o 534
48.0%
Y 15
 
1.3%
e 15
 
1.3%
s 15
 
1.3%

qworktravelcode05
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:06.460591image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.034608379
Min length2

Characters and Unicode

Total characters1117
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 530
96.5%
yes 19
 
3.5%
2023-12-09T21:45:06.683393image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 530
47.4%
o 530
47.4%
Y 19
 
1.7%
e 19
 
1.7%
s 19
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 568
50.9%
Uppercase Letter 549
49.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 530
93.3%
e 19
 
3.3%
s 19
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
N 530
96.5%
Y 19
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1117
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 530
47.4%
o 530
47.4%
Y 19
 
1.7%
e 19
 
1.7%
s 19
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1117
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 530
47.4%
o 530
47.4%
Y 19
 
1.7%
e 19
 
1.7%
s 19
 
1.7%

qworktravelcode06
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:06.790177image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.003642987
Min length2

Characters and Unicode

Total characters1100
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 547
99.6%
yes 2
 
0.4%
2023-12-09T21:45:07.009830image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 547
49.7%
o 547
49.7%
Y 2
 
0.2%
e 2
 
0.2%
s 2
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 551
50.1%
Uppercase Letter 549
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 547
99.3%
e 2
 
0.4%
s 2
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N 547
99.6%
Y 2
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 1100
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 547
49.7%
o 547
49.7%
Y 2
 
0.2%
e 2
 
0.2%
s 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 547
49.7%
o 547
49.7%
Y 2
 
0.2%
e 2
 
0.2%
s 2
 
0.2%

qworktravelcode07
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:07.128360image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.014571949
Min length2

Characters and Unicode

Total characters1106
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 541
98.5%
yes 8
 
1.5%
2023-12-09T21:45:07.365442image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 541
48.9%
o 541
48.9%
Y 8
 
0.7%
e 8
 
0.7%
s 8
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 557
50.4%
Uppercase Letter 549
49.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 541
97.1%
e 8
 
1.4%
s 8
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
N 541
98.5%
Y 8
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1106
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 541
48.9%
o 541
48.9%
Y 8
 
0.7%
e 8
 
0.7%
s 8
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 541
48.9%
o 541
48.9%
Y 8
 
0.7%
e 8
 
0.7%
s 8
 
0.7%

qworktravelcode08
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:07.471429image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1098
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 549
100.0%
2023-12-09T21:45:07.688540image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 549
50.0%
Lowercase Letter 549
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 549
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 549
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1098
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1098
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

qworktravelcode09
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:07.794300image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.010928962
Min length2

Characters and Unicode

Total characters1104
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 543
98.9%
yes 6
 
1.1%
2023-12-09T21:45:08.014383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 543
49.2%
o 543
49.2%
Y 6
 
0.5%
e 6
 
0.5%
s 6
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 555
50.3%
Uppercase Letter 549
49.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 543
97.8%
e 6
 
1.1%
s 6
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
N 543
98.9%
Y 6
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 1104
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 543
49.2%
o 543
49.2%
Y 6
 
0.5%
e 6
 
0.5%
s 6
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 543
49.2%
o 543
49.2%
Y 6
 
0.5%
e 6
 
0.5%
s 6
 
0.5%

qworktravelcode10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:08.115087image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1098
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 549
100.0%
2023-12-09T21:45:08.328713image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 549
50.0%
Lowercase Letter 549
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 549
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 549
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1098
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1098
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

qworktravelcode11
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size46.0 KiB
2023-12-09T21:45:08.452306image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.280510018
Min length2

Characters and Unicode

Total characters1252
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 395
71.9%
yes 154
 
28.1%
2023-12-09T21:45:08.684581image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 395
31.5%
o 395
31.5%
Y 154
 
12.3%
e 154
 
12.3%
s 154
 
12.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 703
56.2%
Uppercase Letter 549
43.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 395
56.2%
e 154
 
21.9%
s 154
 
21.9%
Uppercase Letter
ValueCountFrequency (%)
N 395
71.9%
Y 154
 
28.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 1252
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 395
31.5%
o 395
31.5%
Y 154
 
12.3%
e 154
 
12.3%
s 154
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 395
31.5%
o 395
31.5%
Y 154
 
12.3%
e 154
 
12.3%
s 154
 
12.3%

qworktravelcode12
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:08.791378image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.009107468
Min length2

Characters and Unicode

Total characters1103
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 544
99.1%
yes 5
 
0.9%
2023-12-09T21:45:09.014470image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 544
49.3%
o 544
49.3%
Y 5
 
0.5%
e 5
 
0.5%
s 5
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 554
50.2%
Uppercase Letter 549
49.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 544
98.2%
e 5
 
0.9%
s 5
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
N 544
99.1%
Y 5
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 1103
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 544
49.3%
o 544
49.3%
Y 5
 
0.5%
e 5
 
0.5%
s 5
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1103
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 544
49.3%
o 544
49.3%
Y 5
 
0.5%
e 5
 
0.5%
s 5
 
0.5%

qworktravelcode13
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:09.120639image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.001821494
Min length2

Characters and Unicode

Total characters1099
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 548
99.8%
yes 1
 
0.2%
2023-12-09T21:45:09.343389image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 548
49.9%
o 548
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 550
50.0%
Uppercase Letter 549
50.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 548
99.6%
e 1
 
0.2%
s 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 548
99.8%
Y 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 1099
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 548
49.9%
o 548
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1099
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 548
49.9%
o 548
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

qworktravelcode14
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:09.450634image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.001821494
Min length2

Characters and Unicode

Total characters1099
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 548
99.8%
yes 1
 
0.2%
2023-12-09T21:45:09.669297image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 548
49.9%
o 548
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 550
50.0%
Uppercase Letter 549
50.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 548
99.6%
e 1
 
0.2%
s 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 548
99.8%
Y 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 1099
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 548
49.9%
o 548
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1099
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 548
49.9%
o 548
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

qworktravelcode15
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:09.775166image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.001821494
Min length2

Characters and Unicode

Total characters1099
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 548
99.8%
yes 1
 
0.2%
2023-12-09T21:45:09.995454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 548
49.9%
o 548
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 550
50.0%
Uppercase Letter 549
50.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 548
99.6%
e 1
 
0.2%
s 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 548
99.8%
Y 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 1099
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 548
49.9%
o 548
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1099
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 548
49.9%
o 548
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

qworktravelcode16
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:10.097243image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1098
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 549
100.0%
2023-12-09T21:45:10.310910image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 549
50.0%
Lowercase Letter 549
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 549
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 549
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1098
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1098
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

qworktravelcode17
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:10.417799image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.005464481
Min length2

Characters and Unicode

Total characters1101
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 546
99.5%
yes 3
 
0.5%
2023-12-09T21:45:10.636837image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 546
49.6%
o 546
49.6%
Y 3
 
0.3%
e 3
 
0.3%
s 3
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 552
50.1%
Uppercase Letter 549
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 546
98.9%
e 3
 
0.5%
s 3
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 546
99.5%
Y 3
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 1101
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 546
49.6%
o 546
49.6%
Y 3
 
0.3%
e 3
 
0.3%
s 3
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1101
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 546
49.6%
o 546
49.6%
Y 3
 
0.3%
e 3
 
0.3%
s 3
 
0.3%

qworktravelcode18
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:10.743056image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.007285974
Min length2

Characters and Unicode

Total characters1102
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 545
99.3%
yes 4
 
0.7%
2023-12-09T21:45:10.966887image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 545
49.5%
o 545
49.5%
Y 4
 
0.4%
e 4
 
0.4%
s 4
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 553
50.2%
Uppercase Letter 549
49.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 545
98.6%
e 4
 
0.7%
s 4
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
N 545
99.3%
Y 4
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 1102
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 545
49.5%
o 545
49.5%
Y 4
 
0.4%
e 4
 
0.4%
s 4
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1102
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 545
49.5%
o 545
49.5%
Y 4
 
0.4%
e 4
 
0.4%
s 4
 
0.4%

qworktravelcode19
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:11.074125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.001821494
Min length2

Characters and Unicode

Total characters1099
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 548
99.8%
yes 1
 
0.2%
2023-12-09T21:45:11.296275image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 548
49.9%
o 548
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 550
50.0%
Uppercase Letter 549
50.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 548
99.6%
e 1
 
0.2%
s 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 548
99.8%
Y 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 1099
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 548
49.9%
o 548
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1099
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 548
49.9%
o 548
49.9%
Y 1
 
0.1%
e 1
 
0.1%
s 1
 
0.1%

qworktravelcode20
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:11.399696image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1098
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 549
100.0%
2023-12-09T21:45:11.611107image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 549
50.0%
Lowercase Letter 549
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 549
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 549
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1098
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1098
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

qworktravelcode21
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:11.718135image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.02003643
Min length2

Characters and Unicode

Total characters1109
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 538
98.0%
yes 11
 
2.0%
2023-12-09T21:45:11.938879image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 538
48.5%
o 538
48.5%
Y 11
 
1.0%
e 11
 
1.0%
s 11
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 560
50.5%
Uppercase Letter 549
49.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 538
96.1%
e 11
 
2.0%
s 11
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
N 538
98.0%
Y 11
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1109
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 538
48.5%
o 538
48.5%
Y 11
 
1.0%
e 11
 
1.0%
s 11
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1109
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 538
48.5%
o 538
48.5%
Y 11
 
1.0%
e 11
 
1.0%
s 11
 
1.0%

qworktravelcode22
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:12.047364image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.003642987
Min length2

Characters and Unicode

Total characters1100
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 547
99.6%
yes 2
 
0.4%
2023-12-09T21:45:12.272408image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 547
49.7%
o 547
49.7%
Y 2
 
0.2%
e 2
 
0.2%
s 2
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 551
50.1%
Uppercase Letter 549
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 547
99.3%
e 2
 
0.4%
s 2
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N 547
99.6%
Y 2
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 1100
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 547
49.7%
o 547
49.7%
Y 2
 
0.2%
e 2
 
0.2%
s 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 547
49.7%
o 547
49.7%
Y 2
 
0.2%
e 2
 
0.2%
s 2
 
0.2%

qworktravelcode23
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:12.374249image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1098
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 549
100.0%
2023-12-09T21:45:12.603364image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 549
50.0%
Lowercase Letter 549
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 549
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 549
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1098
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1098
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

qworktravelcode24
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:12.720467image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.029143898
Min length2

Characters and Unicode

Total characters1114
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 533
97.1%
yes 16
 
2.9%
2023-12-09T21:45:12.960476image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 533
47.8%
o 533
47.8%
Y 16
 
1.4%
e 16
 
1.4%
s 16
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 565
50.7%
Uppercase Letter 549
49.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 533
94.3%
e 16
 
2.8%
s 16
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
N 533
97.1%
Y 16
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 1114
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 533
47.8%
o 533
47.8%
Y 16
 
1.4%
e 16
 
1.4%
s 16
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1114
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 533
47.8%
o 533
47.8%
Y 16
 
1.4%
e 16
 
1.4%
s 16
 
1.4%

qworktravelcode25
Text

MISSING 

Distinct2
Distinct (%)0.4%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:13.069683image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.010928962
Min length2

Characters and Unicode

Total characters1104
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 543
98.9%
yes 6
 
1.1%
2023-12-09T21:45:13.296740image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 543
49.2%
o 543
49.2%
Y 6
 
0.5%
e 6
 
0.5%
s 6
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 555
50.3%
Uppercase Letter 549
49.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 543
97.8%
e 6
 
1.1%
s 6
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
N 543
98.9%
Y 6
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 1104
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 543
49.2%
o 543
49.2%
Y 6
 
0.5%
e 6
 
0.5%
s 6
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 543
49.2%
o 543
49.2%
Y 6
 
0.5%
e 6
 
0.5%
s 6
 
0.5%

qworktravelcode26
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing451
Missing (%)45.1%
Memory size45.9 KiB
2023-12-09T21:45:13.398413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1098
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 549
100.0%
2023-12-09T21:45:13.612125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 549
50.0%
Lowercase Letter 549
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 549
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 549
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1098
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1098
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 549
50.0%
o 549
50.0%

qworkcarpark
Text

MISSING 

Distinct6
Distinct (%)3.7%
Missing839
Missing (%)83.9%
Memory size38.8 KiB
2023-12-09T21:45:13.813306image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length34
Mean length22.26086957
Min length5

Characters and Unicode

Total characters3584
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIn a public parking garage or lot
2nd rowOther
3rd rowIn a private garage or parking lot
4th rowOther
5th rowOther
ValueCountFrequency (%)
on 79
10.4%
the 79
10.4%
street 79
10.4%
in 75
9.9%
a 75
9.9%
garage 69
9.1%
or 69
9.1%
lot 59
7.8%
parking 59
7.8%
private 35
4.6%
Other values (7) 83
10.9%
2023-12-09T21:45:14.146504image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
600
16.7%
e 390
10.9%
r 340
9.5%
a 339
9.5%
t 338
9.4%
n 223
 
6.2%
g 207
 
5.8%
i 154
 
4.3%
o 138
 
3.9%
p 118
 
3.3%
Other values (15) 737
20.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2823
78.8%
Space Separator 600
 
16.7%
Uppercase Letter 161
 
4.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 390
13.8%
r 340
12.0%
a 339
12.0%
t 338
12.0%
n 223
7.9%
g 207
7.3%
i 154
 
5.5%
o 138
 
4.9%
p 118
 
4.2%
l 103
 
3.6%
Other values (12) 473
16.8%
Uppercase Letter
ValueCountFrequency (%)
O 86
53.4%
I 75
46.6%
Space Separator
ValueCountFrequency (%)
600
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2984
83.3%
Common 600
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 390
13.1%
r 340
11.4%
a 339
11.4%
t 338
11.3%
n 223
 
7.5%
g 207
 
6.9%
i 154
 
5.2%
o 138
 
4.6%
p 118
 
4.0%
l 103
 
3.5%
Other values (14) 634
21.2%
Common
ValueCountFrequency (%)
600
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3584
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
600
16.7%
e 390
10.9%
r 340
9.5%
a 339
9.5%
t 338
9.4%
n 223
 
6.2%
g 207
 
5.8%
i 154
 
4.3%
o 138
 
3.9%
p 118
 
3.3%
Other values (15) 737
20.6%

qworkparkpay
Text

MISSING 

Distinct29
Distinct (%)18.2%
Missing841
Missing (%)84.1%
Memory size35.5 KiB
2023-12-09T21:45:14.307946image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.352201258
Min length1

Characters and Unicode

Total characters215
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)9.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 110
69.2%
100 6
 
3.8%
30 4
 
2.5%
40 3
 
1.9%
20 3
 
1.9%
25 2
 
1.3%
300 2
 
1.3%
200 2
 
1.3%
250 2
 
1.3%
4 2
 
1.3%
Other values (19) 23
 
14.5%
2023-12-09T21:45:14.596293image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 149
69.3%
1 17
 
7.9%
2 15
 
7.0%
3 12
 
5.6%
5 11
 
5.1%
4 7
 
3.3%
7 2
 
0.9%
6 2
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 215
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 149
69.3%
1 17
 
7.9%
2 15
 
7.0%
3 12
 
5.6%
5 11
 
5.1%
4 7
 
3.3%
7 2
 
0.9%
6 2
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Common 215
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 149
69.3%
1 17
 
7.9%
2 15
 
7.0%
3 12
 
5.6%
5 11
 
5.1%
4 7
 
3.3%
7 2
 
0.9%
6 2
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 215
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 149
69.3%
1 17
 
7.9%
2 15
 
7.0%
3 12
 
5.6%
5 11
 
5.1%
4 7
 
3.3%
7 2
 
0.9%
6 2
 
0.9%

qworkbikepark
Text

MISSING 

Distinct4
Distinct (%)36.4%
Missing989
Missing (%)98.9%
Memory size31.9 KiB
2023-12-09T21:45:14.787744image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length41
Mean length22
Min length5

Characters and Unicode

Total characters242
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)9.1%

Sample

1st rowOn the street
2nd rowOn the street
3rd rowIn a garage/parking lot at your workplace
4th rowOn the street
5th rowOther
ValueCountFrequency (%)
in 7
14.6%
on 5
10.4%
the 5
10.4%
street 5
10.4%
a 4
8.3%
your 4
8.3%
workplace 4
8.3%
dedicated 3
6.2%
bike 3
6.2%
room 3
6.2%
Other values (4) 5
10.4%
2023-12-09T21:45:15.108516image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
15.3%
e 31
12.8%
t 22
 
9.1%
r 20
 
8.3%
o 15
 
6.2%
a 15
 
6.2%
n 13
 
5.4%
i 10
 
4.1%
d 9
 
3.7%
k 8
 
3.3%
Other values (14) 62
25.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 193
79.8%
Space Separator 37
 
15.3%
Uppercase Letter 11
 
4.5%
Other Punctuation 1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 31
16.1%
t 22
11.4%
r 20
10.4%
o 15
 
7.8%
a 15
 
7.8%
n 13
 
6.7%
i 10
 
5.2%
d 9
 
4.7%
k 8
 
4.1%
c 7
 
3.6%
Other values (10) 43
22.3%
Uppercase Letter
ValueCountFrequency (%)
O 7
63.6%
I 4
36.4%
Space Separator
ValueCountFrequency (%)
37
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 204
84.3%
Common 38
 
15.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 31
15.2%
t 22
10.8%
r 20
 
9.8%
o 15
 
7.4%
a 15
 
7.4%
n 13
 
6.4%
i 10
 
4.9%
d 9
 
4.4%
k 8
 
3.9%
O 7
 
3.4%
Other values (12) 54
26.5%
Common
ValueCountFrequency (%)
37
97.4%
/ 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 242
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37
15.3%
e 31
12.8%
t 22
 
9.1%
r 20
 
8.3%
o 15
 
6.2%
a 15
 
6.2%
n 13
 
5.4%
i 10
 
4.1%
d 9
 
3.7%
k 8
 
3.3%
Other values (14) 62
25.6%

qschool
Text

Distinct3
Distinct (%)0.3%
Missing9
Missing (%)0.9%
Memory size81.1 KiB
2023-12-09T21:45:15.295640image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length26
Mean length26.419778
Min length26

Characters and Unicode

Total characters26182
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo, I do not attend school
2nd rowNo, I do not attend school
3rd rowNo, I do not attend school
4th rowNo, I do not attend school
5th rowNo, I do not attend school
ValueCountFrequency (%)
i 991
16.7%
attend 991
16.7%
school 991
16.7%
no 887
14.9%
do 887
14.9%
not 887
14.9%
yes 104
 
1.7%
time 104
 
1.7%
full 67
 
1.1%
part 37
 
0.6%
2023-12-09T21:45:15.606436image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4955
18.9%
o 4643
17.7%
t 3010
11.5%
d 1878
 
7.2%
n 1878
 
7.2%
e 1199
 
4.6%
l 1125
 
4.3%
s 1095
 
4.2%
a 1028
 
3.9%
, 991
 
3.8%
Other values (11) 4380
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18254
69.7%
Space Separator 4955
 
18.9%
Uppercase Letter 1982
 
7.6%
Other Punctuation 991
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 4643
25.4%
t 3010
16.5%
d 1878
10.3%
n 1878
10.3%
e 1199
 
6.6%
l 1125
 
6.2%
s 1095
 
6.0%
a 1028
 
5.6%
c 991
 
5.4%
h 991
 
5.4%
Other values (6) 416
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
I 991
50.0%
N 887
44.8%
Y 104
 
5.2%
Space Separator
ValueCountFrequency (%)
4955
100.0%
Other Punctuation
ValueCountFrequency (%)
, 991
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20236
77.3%
Common 5946
 
22.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 4643
22.9%
t 3010
14.9%
d 1878
9.3%
n 1878
9.3%
e 1199
 
5.9%
l 1125
 
5.6%
s 1095
 
5.4%
a 1028
 
5.1%
I 991
 
4.9%
c 991
 
4.9%
Other values (9) 2398
11.9%
Common
ValueCountFrequency (%)
4955
83.3%
, 991
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26182
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4955
18.9%
o 4643
17.7%
t 3010
11.5%
d 1878
 
7.2%
n 1878
 
7.2%
e 1199
 
4.6%
l 1125
 
4.3%
s 1095
 
4.2%
a 1028
 
3.9%
, 991
 
3.8%
Other values (11) 4380
16.7%

qlevelschool
Text

MISSING 

Distinct5
Distinct (%)4.8%
Missing896
Missing (%)89.6%
Memory size36.3 KiB
2023-12-09T21:45:15.776614image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length30
Median length28
Mean length23.55769231
Min length5

Characters and Unicode

Total characters2450
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCollege or community college
2nd rowCollege or community college
3rd rowCollege or community college
4th rowGraduate school
5th rowCollege or community college
ValueCountFrequency (%)
college 112
30.9%
or 74
20.4%
community 56
15.5%
school 42
 
11.6%
graduate 24
 
6.6%
high 12
 
3.3%
ged 12
 
3.3%
program 12
 
3.3%
other 6
 
1.7%
technical 6
 
1.7%
2023-12-09T21:45:16.072474image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 350
14.3%
l 278
11.3%
e 260
10.6%
258
10.5%
c 172
 
7.0%
g 136
 
5.6%
r 128
 
5.2%
m 124
 
5.1%
t 92
 
3.8%
u 80
 
3.3%
Other values (16) 572
23.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2052
83.8%
Space Separator 258
 
10.5%
Uppercase Letter 140
 
5.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 350
17.1%
l 278
13.5%
e 260
12.7%
c 172
8.4%
g 136
 
6.6%
r 128
 
6.2%
m 124
 
6.0%
t 92
 
4.5%
u 80
 
3.9%
i 80
 
3.9%
Other values (8) 352
17.2%
Uppercase Letter
ValueCountFrequency (%)
C 56
40.0%
G 36
25.7%
H 12
 
8.6%
E 12
 
8.6%
D 12
 
8.6%
O 6
 
4.3%
T 6
 
4.3%
Space Separator
ValueCountFrequency (%)
258
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2192
89.5%
Common 258
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 350
16.0%
l 278
12.7%
e 260
11.9%
c 172
 
7.8%
g 136
 
6.2%
r 128
 
5.8%
m 124
 
5.7%
t 92
 
4.2%
u 80
 
3.6%
i 80
 
3.6%
Other values (15) 492
22.4%
Common
ValueCountFrequency (%)
258
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 350
14.3%
l 278
11.3%
e 260
10.6%
258
10.5%
c 172
 
7.0%
g 136
 
5.6%
r 128
 
5.2%
m 124
 
5.1%
t 92
 
3.8%
u 80
 
3.3%
Other values (16) 572
23.3%

qborough_school
Text

MISSING 

Distinct5
Distinct (%)5.4%
Missing907
Missing (%)90.7%
Memory size34.4 KiB
2023-12-09T21:45:16.243521image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length13
Median length9
Mean length8.731182796
Min length6

Characters and Unicode

Total characters812
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowManhattan
2nd rowManhattan
3rd rowManhattan
4th rowBrooklyn
5th rowManhattan
ValueCountFrequency (%)
manhattan 40
33.6%
the 18
15.1%
bronx 18
15.1%
queens 15
 
12.6%
brooklyn 12
 
10.1%
staten 8
 
6.7%
island 8
 
6.7%
2023-12-09T21:45:16.540555image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 141
17.4%
a 136
16.7%
t 96
11.8%
h 58
 
7.1%
e 56
 
6.9%
o 42
 
5.2%
M 40
 
4.9%
B 30
 
3.7%
r 30
 
3.7%
26
 
3.2%
Other values (11) 157
19.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 667
82.1%
Uppercase Letter 119
 
14.7%
Space Separator 26
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 141
21.1%
a 136
20.4%
t 96
14.4%
h 58
8.7%
e 56
 
8.4%
o 42
 
6.3%
r 30
 
4.5%
s 23
 
3.4%
l 20
 
3.0%
x 18
 
2.7%
Other values (4) 47
 
7.0%
Uppercase Letter
ValueCountFrequency (%)
M 40
33.6%
B 30
25.2%
T 18
15.1%
Q 15
 
12.6%
S 8
 
6.7%
I 8
 
6.7%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 786
96.8%
Common 26
 
3.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 141
17.9%
a 136
17.3%
t 96
12.2%
h 58
7.4%
e 56
 
7.1%
o 42
 
5.3%
M 40
 
5.1%
B 30
 
3.8%
r 30
 
3.8%
s 23
 
2.9%
Other values (10) 134
17.0%
Common
ValueCountFrequency (%)
26
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 812
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 141
17.4%
a 136
16.7%
t 96
11.8%
h 58
 
7.1%
e 56
 
6.9%
o 42
 
5.2%
M 40
 
4.9%
B 30
 
3.7%
r 30
 
3.7%
26
 
3.2%
Other values (11) 157
19.3%

qntacode_school
Text

MISSING 

Distinct54
Distinct (%)58.1%
Missing907
Missing (%)90.7%
Memory size34.0 KiB
2023-12-09T21:45:16.811570image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters372
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)39.8%

Sample

1st rowMN13
2nd rowMN09
3rd rowMN03
4th rowBK09
5th rowMN03
ValueCountFrequency (%)
mn09 6
 
6.5%
mn40 6
 
6.5%
qn38 5
 
5.4%
mn17 5
 
5.4%
mn23 5
 
5.4%
mn13 4
 
4.3%
qn37 3
 
3.2%
bk38 3
 
3.2%
bx06 3
 
3.2%
mn03 2
 
2.2%
Other values (44) 51
54.8%
2023-12-09T21:45:17.199344image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 55
14.8%
M 40
10.8%
3 38
10.2%
B 30
 
8.1%
0 27
 
7.3%
4 24
 
6.5%
2 20
 
5.4%
X 18
 
4.8%
1 18
 
4.8%
Q 15
 
4.0%
Other values (8) 87
23.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 186
50.0%
Decimal Number 186
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 38
20.4%
0 27
14.5%
4 24
12.9%
2 20
10.8%
1 18
9.7%
7 13
 
7.0%
8 13
 
7.0%
9 11
 
5.9%
6 11
 
5.9%
5 11
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
N 55
29.6%
M 40
21.5%
B 30
16.1%
X 18
 
9.7%
Q 15
 
8.1%
K 12
 
6.5%
S 8
 
4.3%
I 8
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 186
50.0%
Common 186
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 38
20.4%
0 27
14.5%
4 24
12.9%
2 20
10.8%
1 18
9.7%
7 13
 
7.0%
8 13
 
7.0%
9 11
 
5.9%
6 11
 
5.9%
5 11
 
5.9%
Latin
ValueCountFrequency (%)
N 55
29.6%
M 40
21.5%
B 30
16.1%
X 18
 
9.7%
Q 15
 
8.1%
K 12
 
6.5%
S 8
 
4.3%
I 8
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 55
14.8%
M 40
10.8%
3 38
10.2%
B 30
 
8.1%
0 27
 
7.3%
4 24
 
6.5%
2 20
 
5.4%
X 18
 
4.8%
1 18
 
4.8%
Q 15
 
4.0%
Other values (8) 87
23.4%

qstudenttravelcode01
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2023-12-09T21:45:17.324784image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.021
Min length2

Characters and Unicode

Total characters2021
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 979
97.9%
yes 21
 
2.1%
2023-12-09T21:45:17.559300image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 979
48.4%
o 979
48.4%
Y 21
 
1.0%
e 21
 
1.0%
s 21
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1021
50.5%
Uppercase Letter 1000
49.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 979
95.9%
e 21
 
2.1%
s 21
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
N 979
97.9%
Y 21
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 2021
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 979
48.4%
o 979
48.4%
Y 21
 
1.0%
e 21
 
1.0%
s 21
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2021
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 979
48.4%
o 979
48.4%
Y 21
 
1.0%
e 21
 
1.0%
s 21
 
1.0%

qstudenttravelcode02
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2023-12-09T21:45:17.672817image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.024
Min length2

Characters and Unicode

Total characters2024
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 976
97.6%
yes 24
 
2.4%
2023-12-09T21:45:17.903669image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 976
48.2%
o 976
48.2%
Y 24
 
1.2%
e 24
 
1.2%
s 24
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1024
50.6%
Uppercase Letter 1000
49.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 976
95.3%
e 24
 
2.3%
s 24
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
N 976
97.6%
Y 24
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 2024
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 976
48.2%
o 976
48.2%
Y 24
 
1.2%
e 24
 
1.2%
s 24
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2024
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 976
48.2%
o 976
48.2%
Y 24
 
1.2%
e 24
 
1.2%
s 24
 
1.2%

qstudenttravelcode03
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:18.015629image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.005
Min length2

Characters and Unicode

Total characters2005
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 995
99.5%
yes 5
 
0.5%
2023-12-09T21:45:18.243025image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 995
49.6%
o 995
49.6%
Y 5
 
0.2%
e 5
 
0.2%
s 5
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1005
50.1%
Uppercase Letter 1000
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 995
99.0%
e 5
 
0.5%
s 5
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N 995
99.5%
Y 5
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 2005
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 995
49.6%
o 995
49.6%
Y 5
 
0.2%
e 5
 
0.2%
s 5
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2005
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 995
49.6%
o 995
49.6%
Y 5
 
0.2%
e 5
 
0.2%
s 5
 
0.2%

qstudenttravelcode04
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:18.345585image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:18.556908image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode05
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:18.663196image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.003
Min length2

Characters and Unicode

Total characters2003
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 997
99.7%
yes 3
 
0.3%
2023-12-09T21:45:18.882621image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 997
49.8%
o 997
49.8%
Y 3
 
0.1%
e 3
 
0.1%
s 3
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1003
50.1%
Uppercase Letter 1000
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 997
99.4%
e 3
 
0.3%
s 3
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 997
99.7%
Y 3
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 2003
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 997
49.8%
o 997
49.8%
Y 3
 
0.1%
e 3
 
0.1%
s 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2003
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 997
49.8%
o 997
49.8%
Y 3
 
0.1%
e 3
 
0.1%
s 3
 
0.1%

qstudenttravelcode06
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:18.984732image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:19.194152image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode07
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:20.710879image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:20.927482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode08
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:21.027199image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:21.237137image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode09
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:21.338519image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:21.545654image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode10
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:21.648471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:21.862014image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode11
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2023-12-09T21:45:21.970415image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.009
Min length2

Characters and Unicode

Total characters2009
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 991
99.1%
yes 9
 
0.9%
2023-12-09T21:45:22.194897image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 991
49.3%
o 991
49.3%
Y 9
 
0.4%
e 9
 
0.4%
s 9
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1009
50.2%
Uppercase Letter 1000
49.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 991
98.2%
e 9
 
0.9%
s 9
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
N 991
99.1%
Y 9
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 2009
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 991
49.3%
o 991
49.3%
Y 9
 
0.4%
e 9
 
0.4%
s 9
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 991
49.3%
o 991
49.3%
Y 9
 
0.4%
e 9
 
0.4%
s 9
 
0.4%

qstudenttravelcode12
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:22.296932image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:22.505011image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode13
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:22.611622image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.002
Min length2

Characters and Unicode

Total characters2002
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 998
99.8%
yes 2
 
0.2%
2023-12-09T21:45:22.831371image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 998
49.9%
o 998
49.9%
Y 2
 
0.1%
e 2
 
0.1%
s 2
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1002
50.0%
Uppercase Letter 1000
50.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 998
99.6%
e 2
 
0.2%
s 2
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 998
99.8%
Y 2
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 2002
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 998
49.9%
o 998
49.9%
Y 2
 
0.1%
e 2
 
0.1%
s 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2002
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 998
49.9%
o 998
49.9%
Y 2
 
0.1%
e 2
 
0.1%
s 2
 
0.1%

qstudenttravelcode14
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:22.935221image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:23.159016image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode15
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:23.261573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:23.476580image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode16
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:23.583321image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.001
Min length2

Characters and Unicode

Total characters2001
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 999
99.9%
yes 1
 
0.1%
2023-12-09T21:45:23.808249image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 999
49.9%
o 999
49.9%
Y 1
 
< 0.1%
e 1
 
< 0.1%
s 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1001
50.0%
Uppercase Letter 1000
50.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 999
99.8%
e 1
 
0.1%
s 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N 999
99.9%
Y 1
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 2001
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 999
49.9%
o 999
49.9%
Y 1
 
< 0.1%
e 1
 
< 0.1%
s 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2001
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 999
49.9%
o 999
49.9%
Y 1
 
< 0.1%
e 1
 
< 0.1%
s 1
 
< 0.1%

qstudenttravelcode17
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:23.919403image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.002
Min length2

Characters and Unicode

Total characters2002
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 998
99.8%
yes 2
 
0.2%
2023-12-09T21:45:24.141675image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 998
49.9%
o 998
49.9%
Y 2
 
0.1%
e 2
 
0.1%
s 2
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1002
50.0%
Uppercase Letter 1000
50.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 998
99.6%
e 2
 
0.2%
s 2
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 998
99.8%
Y 2
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 2002
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 998
49.9%
o 998
49.9%
Y 2
 
0.1%
e 2
 
0.1%
s 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2002
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 998
49.9%
o 998
49.9%
Y 2
 
0.1%
e 2
 
0.1%
s 2
 
0.1%

qstudenttravelcode18
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:24.243844image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:24.454090image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode19
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:24.555292image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:24.764007image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode20
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:24.864997image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:25.081299image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode21
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:25.190264image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.003
Min length2

Characters and Unicode

Total characters2003
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 997
99.7%
yes 3
 
0.3%
2023-12-09T21:45:25.418964image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 997
49.8%
o 997
49.8%
Y 3
 
0.1%
e 3
 
0.1%
s 3
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1003
50.1%
Uppercase Letter 1000
49.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 997
99.4%
e 3
 
0.3%
s 3
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 997
99.7%
Y 3
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 2003
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 997
49.8%
o 997
49.8%
Y 3
 
0.1%
e 3
 
0.1%
s 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2003
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 997
49.8%
o 997
49.8%
Y 3
 
0.1%
e 3
 
0.1%
s 3
 
0.1%

qstudenttravelcode22
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:25.544050image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:25.769745image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode23
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:25.889160image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:26.100905image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudenttravelcode24
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2023-12-09T21:45:26.213469image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.021
Min length2

Characters and Unicode

Total characters2021
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 979
97.9%
yes 21
 
2.1%
2023-12-09T21:45:26.446192image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 979
48.4%
o 979
48.4%
Y 21
 
1.0%
e 21
 
1.0%
s 21
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1021
50.5%
Uppercase Letter 1000
49.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 979
95.9%
e 21
 
2.1%
s 21
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
N 979
97.9%
Y 21
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 2021
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 979
48.4%
o 979
48.4%
Y 21
 
1.0%
e 21
 
1.0%
s 21
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2021
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 979
48.4%
o 979
48.4%
Y 21
 
1.0%
e 21
 
1.0%
s 21
 
1.0%

qstudenttravelcode25
Text

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.8 KiB
2023-12-09T21:45:26.572243image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.021
Min length2

Characters and Unicode

Total characters2021
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 979
97.9%
yes 21
 
2.1%
2023-12-09T21:45:26.801138image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 979
48.4%
o 979
48.4%
Y 21
 
1.0%
e 21
 
1.0%
s 21
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1021
50.5%
Uppercase Letter 1000
49.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 979
95.9%
e 21
 
2.1%
s 21
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
N 979
97.9%
Y 21
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 2021
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 979
48.4%
o 979
48.4%
Y 21
 
1.0%
e 21
 
1.0%
s 21
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2021
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 979
48.4%
o 979
48.4%
Y 21
 
1.0%
e 21
 
1.0%
s 21
 
1.0%

qstudenttravelcode26
Text

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2023-12-09T21:45:26.904082image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2000
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 1000
100.0%
2023-12-09T21:45:27.117213image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1000
50.0%
Lowercase Letter 1000
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1000
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2000
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1000
50.0%
o 1000
50.0%

qstudentpark
Text

MISSING 

Distinct5
Distinct (%)45.5%
Missing989
Missing (%)98.9%
Memory size31.9 KiB
2023-12-09T21:45:27.328994image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length41
Mean length27.54545455
Min length13

Characters and Unicode

Total characters303
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)18.2%

Sample

1st rowIn a public parking garage or lot
2nd rowIn a shared driveway
3rd rowIn a public parking garage or lot
4th rowIn a single family home garage or driveway
5th rowIn a garage or parking lot at your school
ValueCountFrequency (%)
in 7
10.8%
a 7
10.8%
garage 6
9.2%
or 6
9.2%
parking 5
 
7.7%
lot 5
 
7.7%
on 4
 
6.2%
street 4
 
6.2%
the 4
 
6.2%
school 3
 
4.6%
Other values (8) 14
21.5%
2023-12-09T21:45:27.651011image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
17.8%
a 31
10.2%
r 27
 
8.9%
e 23
 
7.6%
o 21
 
6.9%
t 20
 
6.6%
g 18
 
5.9%
n 17
 
5.6%
l 12
 
4.0%
i 11
 
3.6%
Other values (15) 69
22.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 238
78.5%
Space Separator 54
 
17.8%
Uppercase Letter 11
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 31
13.0%
r 27
11.3%
e 23
9.7%
o 21
8.8%
t 20
8.4%
g 18
 
7.6%
n 17
 
7.1%
l 12
 
5.0%
i 11
 
4.6%
h 9
 
3.8%
Other values (12) 49
20.6%
Uppercase Letter
ValueCountFrequency (%)
I 7
63.6%
O 4
36.4%
Space Separator
ValueCountFrequency (%)
54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 249
82.2%
Common 54
 
17.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 31
12.4%
r 27
10.8%
e 23
 
9.2%
o 21
 
8.4%
t 20
 
8.0%
g 18
 
7.2%
n 17
 
6.8%
l 12
 
4.8%
i 11
 
4.4%
h 9
 
3.6%
Other values (14) 60
24.1%
Common
ValueCountFrequency (%)
54
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 303
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54
17.8%
a 31
10.2%
r 27
 
8.9%
e 23
 
7.6%
o 21
 
6.9%
t 20
 
6.6%
g 18
 
5.9%
n 17
 
5.6%
l 12
 
4.0%
i 11
 
3.6%
Other values (15) 69
22.8%

qstudentparkpay
Text

MISSING 

Distinct5
Distinct (%)45.5%
Missing989
Missing (%)98.9%
Memory size31.7 KiB
2023-12-09T21:45:27.774195image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.363636364
Min length1

Characters and Unicode

Total characters15
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)36.4%

Sample

1st row0
2nd row0
3rd row0
4th row15
5th row20
ValueCountFrequency (%)
0 7
63.6%
16 1
 
9.1%
15 1
 
9.1%
20 1
 
9.1%
23 1
 
9.1%
2023-12-09T21:45:28.007215image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8
53.3%
1 2
 
13.3%
2 2
 
13.3%
6 1
 
6.7%
5 1
 
6.7%
3 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8
53.3%
1 2
 
13.3%
2 2
 
13.3%
6 1
 
6.7%
5 1
 
6.7%
3 1
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 15
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8
53.3%
1 2
 
13.3%
2 2
 
13.3%
6 1
 
6.7%
5 1
 
6.7%
3 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8
53.3%
1 2
 
13.3%
2 2
 
13.3%
6 1
 
6.7%
5 1
 
6.7%
3 1
 
6.7%

qstudentbikepark
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing997
Missing (%)99.7%
Memory size31.5 KiB
2023-12-09T21:45:28.171924image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length39
Median length39
Mean length30.33333333
Min length13

Characters and Unicode

Total characters91
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowIn a dedicated bike room in your school
2nd rowIn a dedicated bike room in your school
3rd rowOn the street
ValueCountFrequency (%)
in 4
21.1%
a 2
10.5%
dedicated 2
10.5%
bike 2
10.5%
room 2
10.5%
your 2
10.5%
school 2
10.5%
on 1
 
5.3%
the 1
 
5.3%
street 1
 
5.3%
2023-12-09T21:45:28.454768image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
17.6%
o 10
11.0%
e 9
9.9%
d 6
 
6.6%
i 6
 
6.6%
t 5
 
5.5%
n 5
 
5.5%
r 5
 
5.5%
a 4
 
4.4%
c 4
 
4.4%
Other values (10) 21
23.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 72
79.1%
Space Separator 16
 
17.6%
Uppercase Letter 3
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 10
13.9%
e 9
12.5%
d 6
 
8.3%
i 6
 
8.3%
t 5
 
6.9%
n 5
 
6.9%
r 5
 
6.9%
a 4
 
5.6%
c 4
 
5.6%
h 3
 
4.2%
Other values (7) 15
20.8%
Uppercase Letter
ValueCountFrequency (%)
I 2
66.7%
O 1
33.3%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 75
82.4%
Common 16
 
17.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 10
13.3%
e 9
12.0%
d 6
 
8.0%
i 6
 
8.0%
t 5
 
6.7%
n 5
 
6.7%
r 5
 
6.7%
a 4
 
5.3%
c 4
 
5.3%
h 3
 
4.0%
Other values (9) 18
24.0%
Common
ValueCountFrequency (%)
16
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 91
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
17.6%
o 10
11.0%
e 9
9.9%
d 6
 
6.6%
i 6
 
6.6%
t 5
 
5.5%
n 5
 
5.5%
r 5
 
5.5%
a 4
 
4.4%
c 4
 
4.4%
Other values (10) 21
23.1%

qlanguagepref
Text

MISSING 

Distinct3
Distinct (%)0.5%
Missing399
Missing (%)39.9%
Memory size50.5 KiB
2023-12-09T21:45:28.610404image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.975041597
Min length2

Characters and Unicode

Total characters4192
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEnglish
2nd rowEnglish
3rd rowEnglish
4th rowEnglish
5th rowEnglish
ValueCountFrequency (%)
english 585
97.3%
espa�ol 13
 
2.2%
3
 
0.5%
2023-12-09T21:45:28.887122image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 598
14.3%
l 598
14.3%
s 598
14.3%
n 585
14.0%
g 585
14.0%
i 585
14.0%
h 585
14.0%
p 13
 
0.3%
a 13
 
0.3%
� 13
 
0.3%
Other values (2) 19
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3575
85.3%
Uppercase Letter 598
 
14.3%
Other Symbol 13
 
0.3%
Other Punctuation 6
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 598
16.7%
s 598
16.7%
n 585
16.4%
g 585
16.4%
i 585
16.4%
h 585
16.4%
p 13
 
0.4%
a 13
 
0.4%
o 13
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
E 598
100.0%
Other Symbol
ValueCountFrequency (%)
� 13
100.0%
Other Punctuation
ValueCountFrequency (%)
? 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4173
99.5%
Common 19
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 598
14.3%
l 598
14.3%
s 598
14.3%
n 585
14.0%
g 585
14.0%
i 585
14.0%
h 585
14.0%
p 13
 
0.3%
a 13
 
0.3%
o 13
 
0.3%
Common
ValueCountFrequency (%)
� 13
68.4%
? 6
31.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4179
99.7%
Specials 13
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 598
14.3%
l 598
14.3%
s 598
14.3%
n 585
14.0%
g 585
14.0%
i 585
14.0%
h 585
14.0%
p 13
 
0.3%
a 13
 
0.3%
o 13
 
0.3%
Specials
ValueCountFrequency (%)
� 13
100.0%

qlanguage2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1000
Missing (%)100.0%
Memory size7.9 KiB

qfreight_cmb1
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.8 KiB
2023-12-09T21:45:29.001247image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.079158317
Min length2

Characters and Unicode

Total characters2075
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 919
92.1%
yes 79
 
7.9%
2023-12-09T21:45:29.225763image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 919
44.3%
o 919
44.3%
Y 79
 
3.8%
e 79
 
3.8%
s 79
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1077
51.9%
Uppercase Letter 998
48.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 919
85.3%
e 79
 
7.3%
s 79
 
7.3%
Uppercase Letter
ValueCountFrequency (%)
N 919
92.1%
Y 79
 
7.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 2075
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 919
44.3%
o 919
44.3%
Y 79
 
3.8%
e 79
 
3.8%
s 79
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2075
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 919
44.3%
o 919
44.3%
Y 79
 
3.8%
e 79
 
3.8%
s 79
 
3.8%

qfreight_cmb2
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.9 KiB
2023-12-09T21:45:29.343096image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.253507014
Min length2

Characters and Unicode

Total characters2249
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 745
74.6%
yes 253
 
25.4%
2023-12-09T21:45:29.580484image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 745
33.1%
o 745
33.1%
Y 253
 
11.2%
e 253
 
11.2%
s 253
 
11.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1251
55.6%
Uppercase Letter 998
44.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 745
59.6%
e 253
 
20.2%
s 253
 
20.2%
Uppercase Letter
ValueCountFrequency (%)
N 745
74.6%
Y 253
 
25.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 2249
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 745
33.1%
o 745
33.1%
Y 253
 
11.2%
e 253
 
11.2%
s 253
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2249
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 745
33.1%
o 745
33.1%
Y 253
 
11.2%
e 253
 
11.2%
s 253
 
11.2%

qfreight_cmb3
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size58.0 KiB
2023-12-09T21:45:29.705413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.342685371
Min length2

Characters and Unicode

Total characters2338
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowYes
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 656
65.7%
yes 342
34.3%
2023-12-09T21:45:29.955431image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 656
28.1%
o 656
28.1%
Y 342
14.6%
e 342
14.6%
s 342
14.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1340
57.3%
Uppercase Letter 998
42.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 656
49.0%
e 342
25.5%
s 342
25.5%
Uppercase Letter
ValueCountFrequency (%)
N 656
65.7%
Y 342
34.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 2338
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 656
28.1%
o 656
28.1%
Y 342
14.6%
e 342
14.6%
s 342
14.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2338
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 656
28.1%
o 656
28.1%
Y 342
14.6%
e 342
14.6%
s 342
14.6%

qfreight_cmb4
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size58.2 KiB
2023-12-09T21:45:30.097141image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.490981964
Min length2

Characters and Unicode

Total characters2486
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowYes
3rd rowNo
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 508
50.9%
yes 490
49.1%
2023-12-09T21:45:30.362695image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 508
20.4%
o 508
20.4%
Y 490
19.7%
e 490
19.7%
s 490
19.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1488
59.9%
Uppercase Letter 998
40.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 508
34.1%
e 490
32.9%
s 490
32.9%
Uppercase Letter
ValueCountFrequency (%)
N 508
50.9%
Y 490
49.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 2486
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 508
20.4%
o 508
20.4%
Y 490
19.7%
e 490
19.7%
s 490
19.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2486
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 508
20.4%
o 508
20.4%
Y 490
19.7%
e 490
19.7%
s 490
19.7%

qfreight_cmb5
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size58.0 KiB
2023-12-09T21:45:30.488422image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.29258517
Min length2

Characters and Unicode

Total characters2288
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowNo
3rd rowNo
4th rowYes
5th rowNo
ValueCountFrequency (%)
no 706
70.7%
yes 292
29.3%
2023-12-09T21:45:30.732807image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 706
30.9%
o 706
30.9%
Y 292
12.8%
e 292
12.8%
s 292
12.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1290
56.4%
Uppercase Letter 998
43.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 706
54.7%
e 292
22.6%
s 292
22.6%
Uppercase Letter
ValueCountFrequency (%)
N 706
70.7%
Y 292
29.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 2288
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 706
30.9%
o 706
30.9%
Y 292
12.8%
e 292
12.8%
s 292
12.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 706
30.9%
o 706
30.9%
Y 292
12.8%
e 292
12.8%
s 292
12.8%

qfreight_cmb6
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size58.0 KiB
2023-12-09T21:45:30.857260image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.310621242
Min length2

Characters and Unicode

Total characters2306
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowYes
ValueCountFrequency (%)
no 688
68.9%
yes 310
31.1%
2023-12-09T21:45:31.107806image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 688
29.8%
o 688
29.8%
Y 310
13.4%
e 310
13.4%
s 310
13.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1308
56.7%
Uppercase Letter 998
43.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 688
52.6%
e 310
23.7%
s 310
23.7%
Uppercase Letter
ValueCountFrequency (%)
N 688
68.9%
Y 310
31.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 2306
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 688
29.8%
o 688
29.8%
Y 310
13.4%
e 310
13.4%
s 310
13.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2306
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 688
29.8%
o 688
29.8%
Y 310
13.4%
e 310
13.4%
s 310
13.4%

qfreight_cmb7
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size58.2 KiB
2023-12-09T21:45:31.240357image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.554108216
Min length2

Characters and Unicode

Total characters2549
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes
2nd rowYes
3rd rowYes
4th rowYes
5th rowNo
ValueCountFrequency (%)
yes 553
55.4%
no 445
44.6%
2023-12-09T21:45:31.489360image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Y 553
21.7%
e 553
21.7%
s 553
21.7%
N 445
17.5%
o 445
17.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1551
60.8%
Uppercase Letter 998
39.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 553
35.7%
s 553
35.7%
o 445
28.7%
Uppercase Letter
ValueCountFrequency (%)
Y 553
55.4%
N 445
44.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 2549
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Y 553
21.7%
e 553
21.7%
s 553
21.7%
N 445
17.5%
o 445
17.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2549
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Y 553
21.7%
e 553
21.7%
s 553
21.7%
N 445
17.5%
o 445
17.5%

qfreight_cmb8
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.9 KiB
2023-12-09T21:45:31.608407image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.174348697
Min length2

Characters and Unicode

Total characters2170
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 824
82.6%
yes 174
 
17.4%
2023-12-09T21:45:31.834810image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 824
38.0%
o 824
38.0%
Y 174
 
8.0%
e 174
 
8.0%
s 174
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1172
54.0%
Uppercase Letter 998
46.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 824
70.3%
e 174
 
14.8%
s 174
 
14.8%
Uppercase Letter
ValueCountFrequency (%)
N 824
82.6%
Y 174
 
17.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 2170
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 824
38.0%
o 824
38.0%
Y 174
 
8.0%
e 174
 
8.0%
s 174
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 824
38.0%
o 824
38.0%
Y 174
 
8.0%
e 174
 
8.0%
s 174
 
8.0%

qfreight_cmb9
Text

Distinct2
Distinct (%)0.2%
Missing2
Missing (%)0.2%
Memory size57.7 KiB
2023-12-09T21:45:31.943918image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.049098196
Min length2

Characters and Unicode

Total characters2045
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo
ValueCountFrequency (%)
no 949
95.1%
yes 49
 
4.9%
2023-12-09T21:45:32.166914image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 949
46.4%
o 949
46.4%
Y 49
 
2.4%
e 49
 
2.4%
s 49
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1047
51.2%
Uppercase Letter 998
48.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 949
90.6%
e 49
 
4.7%
s 49
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
N 949
95.1%
Y 49
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 2045
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 949
46.4%
o 949
46.4%
Y 49
 
2.4%
e 49
 
2.4%
s 49
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2045
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 949
46.4%
o 949
46.4%
Y 49
 
2.4%
e 49
 
2.4%
s 49
 
2.4%

allwt
Text

Distinct804
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size66.4 KiB
2023-12-09T21:45:32.502519image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.898
Min length8

Characters and Unicode

Total characters10898
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique655 ?
Unique (%)65.5%

Sample

1st row0.28805089
2nd row1.223591243
3rd row0.409953952
4th row2.398325338
5th row0.767818787
ValueCountFrequency (%)
0.345952549 5
 
0.5%
0.316702696 5
 
0.5%
0.113257637 4
 
0.4%
0.573294838 4
 
0.4%
0.908989001 4
 
0.4%
0.671822633 4
 
0.4%
0.417854598 4
 
0.4%
0.298801127 4
 
0.4%
0.247385124 3
 
0.3%
0.474645514 3
 
0.3%
Other values (794) 960
96.0%
2023-12-09T21:45:32.982105image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1451
13.3%
1 1110
10.2%
. 1000
9.2%
3 980
9.0%
4 971
8.9%
5 971
8.9%
2 954
8.8%
9 888
8.1%
8 875
8.0%
6 867
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9898
90.8%
Other Punctuation 1000
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1451
14.7%
1 1110
11.2%
3 980
9.9%
4 971
9.8%
5 971
9.8%
2 954
9.6%
9 888
9.0%
8 875
8.8%
6 867
8.8%
7 831
8.4%
Other Punctuation
ValueCountFrequency (%)
. 1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10898
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1451
13.3%
1 1110
10.2%
. 1000
9.2%
3 980
9.0%
4 971
8.9%
5 971
8.9%
2 954
8.8%
9 888
8.1%
8 875
8.0%
6 867
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10898
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1451
13.3%
1 1110
10.2%
. 1000
9.2%
3 980
9.0%
4 971
8.9%
5 971
8.9%
2 954
8.8%
9 888
8.1%
8 875
8.0%
6 867
8.0%